{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# MovieLens的数据集——数据探索\n",
    "\n",
    "数据集包含三个主要文件：\n",
    "1. 用户电影打分三元表：u.data\n",
    "4个字段：\n",
    "1）user_id：用户ID\n",
    "2）movie_id：电影ID\n",
    "3）rating：用户打分\n",
    "4）timestamp：表示用户打分的时间，unix seconds since 1/1/1970 UTC\n",
    "\n",
    "2. 用户基本信息表：u.user\n",
    "共5个字段：\n",
    "1）user_id：用户ID\n",
    "2）age：年龄\n",
    "3）gender：性别\n",
    "4）occupation：职业\n",
    "5）zip_code：邮编\n",
    "\n",
    "3. 电影基本信息表：u.item\n",
    "共5 + 19 个字段：\n",
    "1）movie_id：电影ID\n",
    "2）title：电影标题（带年份）\n",
    "3）release_date：电影发布日期\n",
    "4）video_release_date：Video发布日期\n",
    "5）imdb_url：链接\n",
    "\n",
    "6-25）genres（共19维）：\n",
    "'unknown', 'Action', 'Adventure',\n",
    "'Animation', 'Children\\'s', 'Comedy', 'Crime', 'Documentary', 'Drama', 'Fantasy',\n",
    "'Film-Noir', 'Horror', 'Musical', 'Mystery', 'Romance', 'Sci-Fi', 'Thriller', 'War', 'Western'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## import工具包"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "import datetime\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 读入评分数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>user_id</th>\n",
       "      <th>item_id</th>\n",
       "      <th>rating</th>\n",
       "      <th>timestamp</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>196</td>\n",
       "      <td>242</td>\n",
       "      <td>3</td>\n",
       "      <td>881250949</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>186</td>\n",
       "      <td>302</td>\n",
       "      <td>3</td>\n",
       "      <td>891717742</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>22</td>\n",
       "      <td>377</td>\n",
       "      <td>1</td>\n",
       "      <td>878887116</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>244</td>\n",
       "      <td>51</td>\n",
       "      <td>2</td>\n",
       "      <td>880606923</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>166</td>\n",
       "      <td>346</td>\n",
       "      <td>1</td>\n",
       "      <td>886397596</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   user_id  item_id  rating  timestamp\n",
       "0      196      242       3  881250949\n",
       "1      186      302       3  891717742\n",
       "2       22      377       1  878887116\n",
       "3      244       51       2  880606923\n",
       "4      166      346       1  886397596"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#读取数据\n",
    "triplet_cols = ['user_id','item_id', 'rating', 'timestamp'] \n",
    "\n",
    "dpath = './data/'\n",
    "df_triplet = pd.read_csv(dpath +'u.data', sep='\\t', names=triplet_cols, encoding='latin-1')\n",
    "df_triplet.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 100000 entries, 0 to 99999\n",
      "Data columns (total 4 columns):\n",
      "user_id      100000 non-null int64\n",
      "item_id      100000 non-null int64\n",
      "rating       100000 non-null int64\n",
      "timestamp    100000 non-null int64\n",
      "dtypes: int64(4)\n",
      "memory usage: 3.1 MB\n"
     ]
    }
   ],
   "source": [
    "df_triplet.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>user_id</th>\n",
       "      <th>item_id</th>\n",
       "      <th>rating</th>\n",
       "      <th>timestamp</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>196</td>\n",
       "      <td>242</td>\n",
       "      <td>3</td>\n",
       "      <td>1997-12-04 23:55:49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>186</td>\n",
       "      <td>302</td>\n",
       "      <td>3</td>\n",
       "      <td>1998-04-05 03:22:22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>22</td>\n",
       "      <td>377</td>\n",
       "      <td>1</td>\n",
       "      <td>1997-11-07 15:18:36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>244</td>\n",
       "      <td>51</td>\n",
       "      <td>2</td>\n",
       "      <td>1997-11-27 13:02:03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>166</td>\n",
       "      <td>346</td>\n",
       "      <td>1</td>\n",
       "      <td>1998-02-02 13:33:16</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   user_id  item_id  rating           timestamp\n",
       "0      196      242       3 1997-12-04 23:55:49\n",
       "1      186      302       3 1998-04-05 03:22:22\n",
       "2       22      377       1 1997-11-07 15:18:36\n",
       "3      244       51       2 1997-11-27 13:02:03\n",
       "4      166      346       1 1998-02-02 13:33:16"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_triplet['timestamp'].astype('float64')\n",
    "df_triplet['timestamp']=df_triplet['timestamp'].map(datetime.datetime.fromtimestamp) # 时间格式转换\n",
    "df_triplet.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 计算用户数、电影数目"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of users = 943\n",
      "Number of movies = 1682\n"
     ]
    }
   ],
   "source": [
    "n_users = df_triplet['user_id'].unique().shape[0]\n",
    "n_items = df_triplet['item_id'].unique().shape[0]\n",
    "print ('Number of users = ' + str(n_users) + '\\n'+ 'Number of movies = ' + str(n_items) )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 计算每个用户的评分次数\n",
    "看哪些用户最活跃"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "405    737\n",
       "655    685\n",
       "13     636\n",
       "450    540\n",
       "276    518\n",
       "Name: user_id, dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 统计每部电影的评分人数，可看出电影的流行程度，默认是降序排列\n",
    "user_freq = df_triplet['user_id'].value_counts() \n",
    "user_freq.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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xv/4oTXvfdqxXoao+8RaLbl2jbgH3bLVR2n77jj3G8/d+ZNzNkDQCfjN2Rk37CGVa+aHr\nZJmV/2ts0EsTZNyBoD4Z9JpYht7kcZtMJ4Nel+SBvf3Guc4Hee1Z2yd66O9MB30PG1DD5T6hHs10\n0K9Y6+CetpHNJLVlUk3SOpqktqh/Bv0WXeqAHdXBbEioF9O+L09L+w36AUzSxuztB7q28kue292v\nSV6Pg+qhD9o4g37IJuVAGmY7Vp5r3H0b9+tv1r5jj01t20dhEtfFsNs0aX3sNujXW9GTtiG2yyz0\n2z5KP67boNf0GEZo9fBb45s9jTXKz4I2+9y+EU2WmQn6adnxpqWds8BtMR7jWu/D+G90k7rPzEzQ\nb8QkjQ6ncadSny7e37b7s4fNXgY9jNeZxtdYbSaC3kDUtJn0fXZaA3ZWzUTQT4Lt+IfgvR4ok3hF\nxKDbc/V8r9sHpvMf3k9y24aty6DvZQNOaj8m+QO6SV1nozZL/b7Um+nK/GYvCR7mIGCStkkXQb+V\nD1EmYWNs96h+GkdfozBr/X0r0/oGPOjVSG7nToJ+O/V4qmWr7Rj2G+ikBc84RoWDPtewvik9ynW+\nOnAnZZ+fNQa9JHVuJEGf5MNJvpdkIcmxUbyGJGkwQw/6JJcB/wa4HXg/8Ikk7x/260iSBjOKEf3N\nwEJVPVdVfwX8R+DQCF5HkjSAUQT9buDcqvnFViZJGoNU1XCfMLkL+Jmq+qdt/ueBm6vqFy+qdxQ4\n2mavB763yZd8N/Bnm3xsL2Z9Hcx6/8F1MKv9/ztVNbdepR0jeOFFYO+q+T3A+YsrVdVx4PhWXyzJ\nfFUd2OrzTLNZXwez3n9wHcx6/9czilM33wT2J7kuyeXAx4GTI3gdSdIAhj6ir6rXkvxz4PeAy4Df\nqqrvDPt1JEmDGcWpG6rqceDxUTz3GrZ8+qcDs74OZr3/4DqY9f5f0tA/jJUkTRZ/AkGSOjfVQT8L\nP7WQZG+SJ5KcSfKdJJ9q5VclOZXkbLu/spUnyf1tnTyb5Kbx9mA4klyW5FtJHm3z1yV5qvX/S+2D\nf5Jc0eYX2vJ942z3sCTZmeThJN9t+8IHZ3Af+JftGPh2ki8mefus7QebNbVBP0M/tfAa8EtV9T7g\nIHBP6+cx4HRV7QdOt3lYXh/72+0o8MD2N3kkPgWcWTX/OeC+1v+XgSOt/AjwclW9F7iv1evBbwBf\nq6qfAj7A8rqYmX0gyW7gXwAHqurvsnyhx8eZvf1gc6pqKm/AB4HfWzX/WeCz427XNvT7EeA2lr9g\ntquV7QK+16b/LfCJVfVfrzetN5a/i3EauAV4FAjLX47ZcfG+wPLVXh9s0ztavYy7D1vs/zuBP764\nHzO2D6x84/6qtl0fBX5mlvaDrdymdkTPDP7UQvvz80bgKeDaqnoRoN1f06r1uF5+Hfhl4K/b/NXA\nK1X1Wptf3cfX+9+Wv9rqT7P3AEvAb7fTV59P8g5maB+oqv8J/GvgBeBFlrfr08zWfrBp0xz0WaOs\n20uIkvwk8LvAp6vqh5equkbZ1K6XJD8LXKiqp1cXr1G1Blg2rXYANwEPVNWNwF/wxmmatXS3Dtrn\nD4eA64C/DbyD5VNUF+t5P9i0aQ76gX5qoQdJ3sZyyH+hqr7Sil9Ksqst3wVcaOW9rZcPAR9N8jzL\nv4R6C8sj/J1JVr4HsrqPr/e/LX8X8IPtbPAILAKLVfVUm3+Y5eCflX0A4KeBP66qpar6v8BXgL/P\nbO0HmzbNQT8TP7WQJMCDwJmq+rVVi04Ch9v0YZbP3a+U392uvDgIvLry5/00qqrPVtWeqtrH8jb+\nelX9HPAE8LFW7eL+r6yXj7X6Uz2Sq6o/Bc4lub4V3Qr8ETOyDzQvAAeT/EQ7JlbWwczsB1sy7g8J\ntnID7gD+B/B94F+Nuz0j6uM/YPlPzmeBZ9rtDpbPN54Gzrb7q1r9sHw10veBP2T5KoWx92NI6+If\nAY+26fcAvw8sAL8DXNHK397mF9ry94y73UPq+w3AfNsP/hNw5aztA8CvAt8Fvg38e+CKWdsPNnvz\nm7GS1LlpPnUjSRqAQS9JnTPoJalzBr0kdc6gl6TOGfSS1DmDXpI6Z9BLUuf+P1Q+ae8PWyU0AAAA\nAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x113aa5910>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.bar(user_freq.index, user_freq)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 计算每个电影的评分次数\n",
    "看哪些电影最流行(被评分次数最多)\n",
    "基于流行度的推荐可以推荐最流行的电影"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>item_id</th>\n",
       "      <th>rating_times</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>50</td>\n",
       "      <td>583</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>258</th>\n",
       "      <td>258</td>\n",
       "      <td>509</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>100</td>\n",
       "      <td>508</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>181</th>\n",
       "      <td>181</td>\n",
       "      <td>507</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>294</th>\n",
       "      <td>294</td>\n",
       "      <td>485</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     item_id  rating_times\n",
       "50        50           583\n",
       "258      258           509\n",
       "100      100           508\n",
       "181      181           507\n",
       "294      294           485"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 统计每部电影的评分人数，可看出电影的流行程度，默认是降序排列\n",
    "items_rating_times = df_triplet['item_id'].value_counts() \n",
    "#item_freq.head()\n",
    "\n",
    "df_items_sorted_by_rating_times = pd.DataFrame({'item_id':items_rating_times.index, 'rating_times':items_rating_times})\n",
    "df_items_sorted_by_rating_times.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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80+rlO9Fx/MB0qfqx3s+9g2/i2C2npkHs+YySngdARBwD/BNwAXAm8NaIOLPXf2dcjNoK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\nTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x113ac3e90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#按索引排列\n",
    "plt.bar(items_rating_times.index, items_rating_times)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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D8IC7P25mi4E/mNkPgYXA3aH/3cDvzKya2Jb81d0p8OyJ5Ywr688qbdGLiByVToPe3d8B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\nLyKS4RT0IiIZTkEvIpLhFPQiIhnu/wNNNQsmDUwiRQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x113c92150>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#按评分次数排列\n",
    "items_rating_times1 = items_rating_times.copy()\n",
    "items_rating_times1.index = range(items_rating_times1.count()) # 对索引重新赋值，方便画图\n",
    "fig, ax = plt.subplots(1, 1)\n",
    "items_rating_times1.plot(ax=ax, title='Rating Times');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 看看最流行的是哪些电影，与u.item关联"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>item_id</th>\n",
       "      <th>title</th>\n",
       "      <th>release_date</th>\n",
       "      <th>video_release_date</th>\n",
       "      <th>imdb_url</th>\n",
       "      <th>unknown</th>\n",
       "      <th>Action</th>\n",
       "      <th>Adventure</th>\n",
       "      <th>Animation</th>\n",
       "      <th>Children's</th>\n",
       "      <th>...</th>\n",
       "      <th>Fantasy</th>\n",
       "      <th>Film-Noir</th>\n",
       "      <th>Horror</th>\n",
       "      <th>Musical</th>\n",
       "      <th>Mystery</th>\n",
       "      <th>Romance</th>\n",
       "      <th>Sci-Fi</th>\n",
       "      <th>Thriller</th>\n",
       "      <th>War</th>\n",
       "      <th>Western</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Toy Story (1995)</td>\n",
       "      <td>01-Jan-1995</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/M/title-exact?Toy%20Story%2...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>GoldenEye (1995)</td>\n",
       "      <td>01-Jan-1995</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/M/title-exact?GoldenEye%20(...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Four Rooms (1995)</td>\n",
       "      <td>01-Jan-1995</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/M/title-exact?Four%20Rooms%...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Get Shorty (1995)</td>\n",
       "      <td>01-Jan-1995</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/M/title-exact?Get%20Shorty%...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Copycat (1995)</td>\n",
       "      <td>01-Jan-1995</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/M/title-exact?Copycat%20(1995)</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   item_id              title release_date  video_release_date  \\\n",
       "0        1   Toy Story (1995)  01-Jan-1995                 NaN   \n",
       "1        2   GoldenEye (1995)  01-Jan-1995                 NaN   \n",
       "2        3  Four Rooms (1995)  01-Jan-1995                 NaN   \n",
       "3        4  Get Shorty (1995)  01-Jan-1995                 NaN   \n",
       "4        5     Copycat (1995)  01-Jan-1995                 NaN   \n",
       "\n",
       "                                            imdb_url  unknown  Action  \\\n",
       "0  http://us.imdb.com/M/title-exact?Toy%20Story%2...        0       0   \n",
       "1  http://us.imdb.com/M/title-exact?GoldenEye%20(...        0       1   \n",
       "2  http://us.imdb.com/M/title-exact?Four%20Rooms%...        0       0   \n",
       "3  http://us.imdb.com/M/title-exact?Get%20Shorty%...        0       1   \n",
       "4  http://us.imdb.com/M/title-exact?Copycat%20(1995)        0       0   \n",
       "\n",
       "   Adventure  Animation  Children's   ...     Fantasy  Film-Noir  Horror  \\\n",
       "0          0          1           1   ...           0          0       0   \n",
       "1          1          0           0   ...           0          0       0   \n",
       "2          0          0           0   ...           0          0       0   \n",
       "3          0          0           0   ...           0          0       0   \n",
       "4          0          0           0   ...           0          0       0   \n",
       "\n",
       "   Musical  Mystery  Romance  Sci-Fi  Thriller  War  Western  \n",
       "0        0        0        0       0         0    0        0  \n",
       "1        0        0        0       0         1    0        0  \n",
       "2        0        0        0       0         1    0        0  \n",
       "3        0        0        0       0         0    0        0  \n",
       "4        0        0        0       0         1    0        0  \n",
       "\n",
       "[5 rows x 24 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#读取数据\n",
    "item_cols = ['item_id', 'title', 'release_date', 'video_release_date', 'imdb_url', 'unknown', 'Action', 'Adventure',\n",
    " 'Animation', 'Children\\'s', 'Comedy', 'Crime', 'Documentary', 'Drama', 'Fantasy',\n",
    " 'Film-Noir', 'Horror', 'Musical', 'Mystery', 'Romance', 'Sci-Fi', 'Thriller', 'War', 'Western'] \n",
    "\n",
    "dpath = './data/'\n",
    "df_items = pd.read_csv(dpath +'u.item', sep='|', names=item_cols,encoding='latin-1') \n",
    "df_items.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>item_id</th>\n",
       "      <th>rating_times</th>\n",
       "      <th>title</th>\n",
       "      <th>release_date</th>\n",
       "      <th>video_release_date</th>\n",
       "      <th>imdb_url</th>\n",
       "      <th>unknown</th>\n",
       "      <th>Action</th>\n",
       "      <th>Adventure</th>\n",
       "      <th>Animation</th>\n",
       "      <th>...</th>\n",
       "      <th>Film-Noir</th>\n",
       "      <th>Horror</th>\n",
       "      <th>Musical</th>\n",
       "      <th>Mystery</th>\n",
       "      <th>Romance</th>\n",
       "      <th>Sci-Fi</th>\n",
       "      <th>Thriller</th>\n",
       "      <th>War</th>\n",
       "      <th>Western</th>\n",
       "      <th>ranking_rating_times</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>50</td>\n",
       "      <td>583</td>\n",
       "      <td>Star Wars (1977)</td>\n",
       "      <td>01-Jan-1977</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/M/title-exact?Star%20Wars%2...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>258</td>\n",
       "      <td>509</td>\n",
       "      <td>Contact (1997)</td>\n",
       "      <td>11-Jul-1997</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/Title?Contact+(1997/I)</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>100</td>\n",
       "      <td>508</td>\n",
       "      <td>Fargo (1996)</td>\n",
       "      <td>14-Feb-1997</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/M/title-exact?Fargo%20(1996)</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>181</td>\n",
       "      <td>507</td>\n",
       "      <td>Return of the Jedi (1983)</td>\n",
       "      <td>14-Mar-1997</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/M/title-exact?Return%20of%2...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>294</td>\n",
       "      <td>485</td>\n",
       "      <td>Liar Liar (1997)</td>\n",
       "      <td>21-Mar-1997</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/Title?Liar+Liar+(1997)</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   item_id  rating_times                      title release_date  \\\n",
       "0       50           583           Star Wars (1977)  01-Jan-1977   \n",
       "1      258           509             Contact (1997)  11-Jul-1997   \n",
       "2      100           508               Fargo (1996)  14-Feb-1997   \n",
       "3      181           507  Return of the Jedi (1983)  14-Mar-1997   \n",
       "4      294           485           Liar Liar (1997)  21-Mar-1997   \n",
       "\n",
       "   video_release_date                                           imdb_url  \\\n",
       "0                 NaN  http://us.imdb.com/M/title-exact?Star%20Wars%2...   \n",
       "1                 NaN          http://us.imdb.com/Title?Contact+(1997/I)   \n",
       "2                 NaN    http://us.imdb.com/M/title-exact?Fargo%20(1996)   \n",
       "3                 NaN  http://us.imdb.com/M/title-exact?Return%20of%2...   \n",
       "4                 NaN          http://us.imdb.com/Title?Liar+Liar+(1997)   \n",
       "\n",
       "   unknown  Action  Adventure  Animation          ...           Film-Noir  \\\n",
       "0        0       1          1          0          ...                   0   \n",
       "1        0       0          0          0          ...                   0   \n",
       "2        0       0          0          0          ...                   0   \n",
       "3        0       1          1          0          ...                   0   \n",
       "4        0       0          0          0          ...                   0   \n",
       "\n",
       "   Horror  Musical  Mystery  Romance  Sci-Fi  Thriller  War  Western  \\\n",
       "0       0        0        0        1       1         0    1        0   \n",
       "1       0        0        0        0       1         0    0        0   \n",
       "2       0        0        0        0       0         1    0        0   \n",
       "3       0        0        0        1       1         0    1        0   \n",
       "4       0        0        0        0       0         0    0        0   \n",
       "\n",
       "   ranking_rating_times  \n",
       "0                     0  \n",
       "1                     1  \n",
       "2                     2  \n",
       "3                     3  \n",
       "4                     4  \n",
       "\n",
       "[5 rows x 26 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 根据频次大小依次取电影信息\n",
    "df_items_sorted_by_rating_times_merge = pd.merge(df_items_sorted_by_rating_times, df_items, how='left', left_on='item_id', right_on='item_id')\n",
    "df_items_sorted_by_rating_times_merge['ranking_rating_times']=range(items_rating_times.count()) # 加上排名,数字越小，排在越前面\n",
    "\n",
    "df_items_sorted_by_rating_times_merge.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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NTz75pPbu3atq1app06ZNatCggSRp06ZNioyM1C+//KKqVavetI/U1FQFBAQoJSWFw14A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\nAADAUgg/AADAUgg/AADAUgg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Go0ePVuvWrVW7du1bep+NiYnRzp07JUkZGRl65ZVXVLZs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iIiImBnZ0et29jYwNvbu94GPxMmTMC0adMwadIk5Ofnw8bGBsbGxjhw4ADy8/OxdOnSWtuUkpJC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\neYbwjX7sdwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11a0f0ad0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 前二十大流行电影\n",
    "popular_items_count_top_20 = df_items_sorted_by_rating_times_merge.iloc[0:20]['rating_times']\n",
    "popular_items_top_20_titles =  df_items_sorted_by_rating_times_merge.iloc[0:20]['title']\n",
    "\n",
    "objects = (list(popular_items_top_20_titles))\n",
    "y_pos = np.arange(len(objects))\n",
    "performance = list(popular_items_count_top_20)\n",
    " \n",
    "plt.rcdefaults()    \n",
    "plt.bar(y_pos, performance, align='center', alpha=0.5)\n",
    "plt.xticks(y_pos, objects, rotation='vertical')\n",
    "plt.ylabel('Rating Count')\n",
    "plt.title('Most popular Movies')\n",
    " \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 计算每个电影的受欢迎程度\n",
    "看哪些电影的平均评分分数最高（总评分？）\n",
    "基于受欢迎的程度可以推荐最受欢迎的电影"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>item_id</th>\n",
       "      <th>mean_rating</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>item_id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1293</th>\n",
       "      <td>1293</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1467</th>\n",
       "      <td>1467</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1653</th>\n",
       "      <td>1653</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>814</th>\n",
       "      <td>814</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1122</th>\n",
       "      <td>1122</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         item_id  mean_rating\n",
       "item_id                      \n",
       "1293        1293          5.0\n",
       "1467        1467          5.0\n",
       "1653        1653          5.0\n",
       "814          814          5.0\n",
       "1122        1122          5.0"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "items_mean_rating = df_triplet['rating'].groupby(df_triplet['item_id']).mean()\n",
    "items_mean_rating = items_mean_rating.sort_values(ascending = False)\n",
    "\n",
    "df_items_sorted_by_mean_rating = pd.DataFrame({'item_id':items_mean_rating.index, 'mean_rating':items_mean_rating})\n",
    "df_items_sorted_by_mean_rating.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>item_id</th>\n",
       "      <th>mean_rating</th>\n",
       "      <th>rating_times</th>\n",
       "      <th>title</th>\n",
       "      <th>release_date</th>\n",
       "      <th>video_release_date</th>\n",
       "      <th>imdb_url</th>\n",
       "      <th>unknown</th>\n",
       "      <th>Action</th>\n",
       "      <th>Adventure</th>\n",
       "      <th>...</th>\n",
       "      <th>Horror</th>\n",
       "      <th>Musical</th>\n",
       "      <th>Mystery</th>\n",
       "      <th>Romance</th>\n",
       "      <th>Sci-Fi</th>\n",
       "      <th>Thriller</th>\n",
       "      <th>War</th>\n",
       "      <th>Western</th>\n",
       "      <th>ranking_rating_times</th>\n",
       "      <th>ranking_mean_rate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1293</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3</td>\n",
       "      <td>Star Kid (1997)</td>\n",
       "      <td>16-Jan-1998</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/M/title-exact?imdb-title-12...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1450</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1467</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2</td>\n",
       "      <td>Saint of Fort Washington, The (1993)</td>\n",
       "      <td>01-Jan-1993</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/M/title-exact?Saint%20of%20...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1483</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1653</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1</td>\n",
       "      <td>Entertaining Angels: The Dorothy Day Story (1996)</td>\n",
       "      <td>27-Sep-1996</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/M/title-exact?Entertaining%...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1652</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>814</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1</td>\n",
       "      <td>Great Day in Harlem, A (1994)</td>\n",
       "      <td>01-Jan-1994</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/M/title-exact?Great%20Day%2...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1661</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1122</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1</td>\n",
       "      <td>They Made Me a Criminal (1939)</td>\n",
       "      <td>01-Jan-1939</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/M/title-exact?They%20Made%2...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1615</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 28 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   item_id  mean_rating  rating_times  \\\n",
       "0     1293          5.0             3   \n",
       "1     1467          5.0             2   \n",
       "2     1653          5.0             1   \n",
       "3      814          5.0             1   \n",
       "4     1122          5.0             1   \n",
       "\n",
       "                                               title release_date  \\\n",
       "0                                    Star Kid (1997)  16-Jan-1998   \n",
       "1               Saint of Fort Washington, The (1993)  01-Jan-1993   \n",
       "2  Entertaining Angels: The Dorothy Day Story (1996)  27-Sep-1996   \n",
       "3                      Great Day in Harlem, A (1994)  01-Jan-1994   \n",
       "4                     They Made Me a Criminal (1939)  01-Jan-1939   \n",
       "\n",
       "   video_release_date                                           imdb_url  \\\n",
       "0                 NaN  http://us.imdb.com/M/title-exact?imdb-title-12...   \n",
       "1                 NaN  http://us.imdb.com/M/title-exact?Saint%20of%20...   \n",
       "2                 NaN  http://us.imdb.com/M/title-exact?Entertaining%...   \n",
       "3                 NaN  http://us.imdb.com/M/title-exact?Great%20Day%2...   \n",
       "4                 NaN  http://us.imdb.com/M/title-exact?They%20Made%2...   \n",
       "\n",
       "   unknown  Action  Adventure        ...          Horror  Musical  Mystery  \\\n",
       "0        0       0          1        ...               0        0        0   \n",
       "1        0       0          0        ...               0        0        0   \n",
       "2        0       0          0        ...               0        0        0   \n",
       "3        0       0          0        ...               0        0        0   \n",
       "4        0       0          0        ...               0        0        0   \n",
       "\n",
       "   Romance  Sci-Fi  Thriller  War  Western  ranking_rating_times  \\\n",
       "0        0       1         0    0        0                  1450   \n",
       "1        0       0         0    0        0                  1483   \n",
       "2        0       0         0    0        0                  1652   \n",
       "3        0       0         0    0        0                  1661   \n",
       "4        0       0         0    0        0                  1615   \n",
       "\n",
       "   ranking_mean_rate  \n",
       "0                  0  \n",
       "1                  1  \n",
       "2                  2  \n",
       "3                  3  \n",
       "4                  4  \n",
       "\n",
       "[5 rows x 28 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 根据频次大小依次取电影信息\n",
    "df_items_sorted_by_mean_rating_merge = pd.merge(df_items_sorted_by_mean_rating, df_items_sorted_by_rating_times_merge, how='left', left_on='item_id', right_on='item_id')\n",
    "df_items_sorted_by_mean_rating_merge['ranking_mean_rate']=range(items_mean_rating.count()) # 加上排名,数字越小，排在越前面\n",
    "\n",
    "df_items_sorted_by_mean_rating_merge.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "原来这些全 5 分的电影都只有 1-3 个评分！这就把排名排上去了！\n",
    "看来平均分不靠谱，得把评分人次也考虑进去！（总评分？）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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TtS+sS21ex9yuDQC5eqSlVatWuvPOO1W1alU1a9ZM8+bNkyS98847F11/0KBBSk5O9j72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\nxMRExwKc2wZkdFwuHuVxjfT0dHvyySc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dOxc7d+6EqampzHSBkngYLS0tAIC+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TnhxYsXsLb+/9g787ga8/f/v85p0a5kSRQtqJAthRqUpY2xDmN8IqIxM5RIMfYsY42yTLZSGIQw\nDZKUUiTZCu1abGGyV6jT9fujb/ev42Tp3Od0TuM8H4/zGOd9n8d1X5055z7v+3pf79erM8rKyoSK\nCwCtW7fGyZMnYWlpCQ0NDaSmpqJjx474+++/sW7dOiQmJtY75rhx41BRUYHjx4/XeXzEiBFQVFQU\nyqTt8uXLCA4ORnh4OExMTODi4oLx48dDV1dXJMtD4tCcUFNTQ1paGgwNDSEnJ4fi4mKhFIzr4kt+\nVzWwsZio3b9QGw6HAyUlJRgbG6N///4C36nPoaioiPz8fLRp04YZU1ZWRnZ2NvT09ITO9WPS09Ox\nYcMGXLt2DVVVVejZsyd8fX3RtWtXoWP+9ttviIuLg5+fHyZNmoRt27bh4cOH2LFjB9asWYOJEyeK\nLH9p5vTp0ygpKYGLiwsztmrVKqxYsQKVlZWws7PD4cOHpdYN+8WLF3BwcEB+fj6eP38OAwMDPHjw\nAN27d0d0dDSrpf2qqipUVVUxuknh4eFITEyEsbExZsyYIdTvTG3Onz+P8+fP1ynmFxwczCp2QyCb\ntEiYGkVVAHV6WSgrK2PLli187s/1oXfv3li5ciXs7e0xcuRIaGho4I8//kBgYCCOHj3KqqlQHBOi\nGzduoG/fvhg2bBh8fHwYuenMzEysW7cOp06dwqVLl1g55paVleHQoUMIDg5GSkoKeDwe/P39MXXq\nVFYXm3bt2uHXX3+Fr6+v0DE+ZsiQIXjy5Al69eqF0NBQjB8//pNqqtJ4wTEwMMCzZ89QVlYGLS0t\nEBFevnwJFRUVqKmp4enTpzA0NERcXNxXTzjqmrzV9Cs0hKM5G/T19REWFoaBAwdCQ0MD169fh7Gx\nMfbt24eDBw/i9OnTkk6xQbCzs8OYMWMYccFLly7hu+++g5+fH0xNTbFw4UI4OjoK5Q3UUNYaVVVV\niIqKwvXr15lJrZOT02f7RiTN8uXL4efnBwsLC7Ru3VpAYO9TN4tShSTLPDKqezTy8/OJw+HQ1atX\n+fbMP3r0iHXJe//+/RQSEkJE1Vtja8rSSkpKdOjQIVaxLSwsKCoqioiIRowYQS4uLvTgwQPy8fEh\nQ0NDoeNGRkbWWT5v0aIFnTx5klXOH5OZmUnz5s0jHR0dUlJSouHDhwsdSxyaE8XFxeTr60tjx44l\nLpdLjo6ONHLkyDof0shff/1FAwcO5OsfyMnJITs7Ozp06BDdv3+frK2tacyYMV8dk8PhkJOTE40a\nNYp5yMvL09ChQ/nG2MLj8SgrK4suXrxI8fHxfA9hUVVVZXq22rRpwyzdst2C29ho0aIFXb9+nXnu\n5eXF1yt06tQpMjY2Fip2bcG0zz1EvRxXW+qADWfOnKGLFy8yz7du3UrdunWjCRMmMHowwqKjo0Nh\nYWFsU5QoskrLN0ZZWRkyMzOhr6/PerfFgQMHUFFRAVdXV9y4cQP29vYoKSmBoqIi9u7di/Hjxwsd\nu7y8HFFRUcjNzQURoWPHjhg6dGid2xdFAY/HQ2RkJIKDg7+4LfBTuLm5oXfv3pgxY4aIs6vGwMAA\nqamp0NbWFkt8cWBkZIRjx46he/fufOM3btzAmDFjcO/ePVy6dAljxozB48ePvyqmOHa0fExycjJ+\n+uknFBYWClRA2eyyMDc3x5YtWzBgwAAMHToU5ubm2LBhAwIDA7Fu3To8ePBA6JwbE8rKysjKymLM\nOC0tLTF27Fj4+PgAqF66NDMzQ2lpab1jf+2yJyD80uemTZugp6eHsWPHAgAmTZqEAwcOQF9fH//8\n8w+rHXhdu3bF2rVr4eTkhPT0dFhYWGDu3LmIjY2Fqakpq8+1trY2UlJSRGLCKylkkxYp4VM/lLXX\n/qW99C3KCVFj5I8//oC/vz+cnZ3FojlRm3fv3kFJSUlk8cSFiooKEhISYGFhwTd+9epVDBgwAGVl\nZSgoKECXLl3w9u1bCWUpSPfu3dGxY0csX768zjJ6jYFgfdm0aRPk5OTg4eGBuLg4ODs7g8fjobKy\nEv7+/vD09BRF+lKPkZERtm/fDnt7e7x9+xba2tqIjY2FtbU1AOD69euwt7fHs2fPJJxp3RgZGSE0\nNBQ2NjaIjY3FqFGjsG/fPhw9ehTPnj3DmTNnhI6tpqaG27dvo3379li2bBlu376No0eP4vr163By\nckJxcbHQsX19faGmpobFixcLHUPSyCYtUkJtt+Da1HYQtrGxwYkTJ766Oa20tBRr165FREQECgoK\nwOFwYGBggLFjx8Lb21tsVYtvFXE4A9emqqoKq1atQlBQEJ48eYLs7GwYGhpi8eLFaN++Pdzc3FjF\nFwfOzs4oLi7G7t27GTfqGzduYPr06dDR0cE///yDyMhI/P7770hPT5dwtv8fVVVV3Lp1C8bGxmI9\nT1FREVJTU2FkZMTKmLKx4evri7///hu///47Tp8+jUuXLuHevXtMQ/bOnTsRFhYmVDN/fSqlwoqp\n1W789vLywtu3b7Fr1y5kZWWhb9++rDS7mjVrhsTERJiZmcHGxgaTJk2Cu7s7CgoKYGZmxmrzhKen\nJ8LCwmBubg5zc3OBGytheogaGpkirpRw7tw5LFy4EKtWrYKlpSUAICUlBYsWLcLixYvRtGlT/Pzz\nz/D29v4q1dYPHz5gwIABuH37NhwdHTF8+HAQETIyMrBq1SqcOXMGCQkJAh/ar2HOnDlf9brG8AUQ\nJfn5+WKNv3LlSoSGhmLdunWYPn06M961a1ds2rRJKicte/bsgYuLC3r16sV81iorKzFo0CDmc6ym\npoaNGzdKMk0BrKyskJubK9ZJy7t376Cvr88skXxLLF26FI8ePYKHhwd0dHSwf/9+vh1kBw8exPDh\nw4WK/bGb+sc3g7WrZsIu82lqauLRo0fQ09NDVFQUli1bxsSuqKgQKmYNNjY2mDNnDqytrZGSkoLD\nhw8DALKzs+stIPkxaWlpzFLt7du3WcWSGJJppZHxMZ07d6akpCSB8cTERMbY69y5c19tnrh582Zq\n1aoVZWZmChzLyMigVq1aMeJZ9WXgwIF8D3l5ebKysuIbYyOIJ6NujIyMKCYmhoj4Ba0yMjJIU1NT\n6LjFxcX0v//9j1q3bk1ycnJi0Q7JyMigkydP0okTJ+r8TEoDtQX1IiIiyMzMjEJCQuoU3hOWyspK\n8vPzI11dXT4jxkWLFtHu3btF9afI+D/OnTtHPXv2pKioKHr16hW9fv2aoqKiyMLCgqKjo4WO6+7u\nTkZGRuTs7EyampqMMGB4eDiZm5uzyrmwsJCcnZ3J3Nyc7zMxe/ZsmjVrFqvY/wVky0NSgrKyMq5e\nvYouXbrwjaenp8PS0hLl5eUoLCyEqanpV5UHBwwYgHHjxjFbCj9my5YtOHr0KOLj41nnXlvG+lvn\nwYMH+Pvvv+u0NWBbeVJWVkZmZibatWvH957fvXsXlpaWQveEODo6oqioCDNnzqyzf2PEiBGs8m4s\nfGqJtobaS7XC3qH7+fkhNDQUfn5+mD59OmMVEB4ejk2bNuHy5cts/gQZH9GlSxcEBQXBxsaGb/zi\nxYtwd3dHRkaGUHHfv3+P9evX4/79+3Bzc2Oq4+vXr4eqqip+/fVX1rk3FFVVVTh16hT27NmDEydO\nSDqdLyJbHpISevXqhXnz5iEsLIzRn3j27Bl8fHwYH56cnJyvLg/evXsXAwcO/ORxW1tb+Pn5sc67\nISgvLxcoudZlqPi1hIaGonnz5nB2dgYA+Pj4YOfOnTAzM8PBgweF3lFw/vx5fP/99zAwMEBWVha6\ndOmCgoICEBErXZkaOnfujIsXLwrkd+TIEaZfRBgSExNx8eJFgR0+ooDH42Hv3r2fFLOKjY0VKm5F\nRQXc3d2xePFikU2Wxb28BwBhYWHYuXMnBg0axLfLzNzcHJmZmWI//7dGXl5enU3TTZs2FVqwEwCa\nNGmCRYsWCYzPmzdP6Jh1IeprX21ycnIQHByM0NBQvHjxAvb29iKJK25kkxYpYc+ePRgxYgTatm3L\nZ4ZnaGiIkydPAgDevn371V3fL1++/OzWWG1tbak2fSsrK4OPjw/Cw8PrNAhjY+y1evVqxiX68uXL\n2Lp1KzZv3ox//vkHXl5eiIiIECruggULMHfuXPj5+UFdXR3Hjh1Dy5YtMXHiRD5XcGFZunQpXFxc\n8PDhQ1RVVSEiIgJZWVkICwtj5SKtp6f3yeoCWzw9PbF37144OzujS5cuAlUcYVFQUMDx48dFugui\n9mQwISEB/fr1Y1RJa6isrMSlS5eEntg+fPiwzj6Zqqoq1r0QMgTp3bs3Zs+ejf3796N169YAgOLi\nYsydO5epjghDeHj4Z4+zcRsvLS2Fr6+vWK595eXlCA8Px549e5CcnAwej4dNmzZh6tSpUFNTEzpu\ngyLJtSkZ/FRVVdGZM2coICCANm/eTFFRUcTj8YSKxeVy6enTp588XlxcLLJ+hdr9FaLi119/JVNT\nUzpy5AgpKytTcHAwrVixgtq2bUv79+9nFVtZWZkKCwuJiMjHx4dcXFyIiOj27dvUvHlzoeOqqakx\nImqampp0+/ZtIiK6efMmtWvXjlXONURFRVH//v1JVVWVlJWVydrams6ePcsq5tmzZ2no0KGUn58v\nkhxro62tTadOnRJ5XCIiV1dX2rhxo1hic7ncOr3A/v33X1bfm169etG+ffuIiP97s2zZMrKxsRE6\nroy6ycnJoS5dupCCggIZGRmRkZERKSgoUOfOnSknJ0fouEpKSnwPBQUF4nA4JC8vL7Shaw3iuPZd\nuXKFpk+fThoaGmRhYUGbN2+m4uLiRmcWS0Qkq7RIERwOBw4ODiK5KyciDBo0SOBOsYbKykqhY38s\nk01EyMzMFOipYCORHRkZycidT506Fd999x2MjY3Rrl07HDhwgJVHi5qaGkpKSqCvr4/o6Gh4eXkB\nAJSUlFhZyquqquL9+/cAAF1dXeTl5TEiU//++6/QcYHqu6vExERYWlqKpA9JS0uLr+pRWloKIyMj\nqKioCOwoY7N9U1FRUWw7cIyNjbFixQpcunQJvXr1gqqqKt9xNro49H+9Kx9TUlIicJ76IK5q2X8B\ncWgPGRsbIy0tDefOnUNmZiaICGZmZhg8eDCrqt/H1wkiwu3bt+Hp6VnnslF9EMe1r1+/fpg1axZS\nUlIYa5TGiqwRV4oQpZHV8uXLv+p1S5curVdc4PMNi6JoVgSqJxZ37txBu3bt0LZtW0RERMDS0hL5\n+fno2rUrKyGyiRMnIjMzEz169MDBgwdRVFQEbW1tRjdC2K2AI0eOhLOzM6ZPnw4fHx8cP34crq6u\niIiIgJaWFmJiYoTOGaieVGVkZIhEZDA0NPSrXzt58mShz7Nx40bcu3cPW7duFdnSUA3i0MUZPXo0\nAODkyZNwcHBAkyZNmGM8Hg9paWno1KkToqKi6p/w/3H27FmsXr2az4hxyZIlGDp0qNAxGyuNUXvo\nc6SkpGDKlCm4c+eO0DHEce0bOnQokpOTMXz4cLi4uMDe3h4cDgcKCgoiMYttSGSVFinhS0ZW9UWY\nycjX0hANi4aGhigoKEC7du1gZmaG8PBwWFpaIjIyEpqamqxib9u2DYsWLcL9+/dx7Ngxpvfn2rVr\nmDBhgtBx/f39mQvKsmXL8PbtWxw+fBjGxsbYtGkTq5yBaj2We/fuiWTSwmYiUh8SExMRFxeHM2fO\noHPnzgJVHGH7hwDxfA5rmjaJCOrq6nzmlIqKiujTpw+fRo4w2NvbN5qmR3HTENpDDelqrKSkhKKi\nIlYxxHHti46Oxv379xESEoJffvkF5eXljM2KqG8mxI2s0iIltG7dGuvWreOzav+WkcmdCxIdHQ1f\nX1+sWLGizuUQYXcVyMnJ4fHjx2jZsiXfeElJCVq2bMmqYvYlnyA2Pio1fPjwAfn5+TAyMvrkcmh9\nWb58Oby9vVktBcn4MsbGxtixYwcGDRrEt40/MzMTffv2xYsXL1jFF5ercXR0NN9zIsLjx48REBCA\nFi1aCByvDw1x7Tt37hyCg4Nx4sQJxkNp7NixItnlKG5kkxYp4b9gZCVORCF3/vEdUGNTIq1teV/7\n4st2OY7L5aK4uFhg0vLo0SMYGRmx6vMRJ2VlZZg1axaz1FWztODh4QFdXV3Mnz+f9TmePXuGrKws\ncPjbCuAAACAASURBVDgcdOzYkZEjqA8f9w99Djb9Q40RcWkP1SCum8Ha38UaNDQ0YGdnh4CAAOjp\n6YnsXOK0enjx4gX279+P4OBgpKWlsbpBaShky0NSwrRp0/DXX381aiMrcSIKufP27duLrOdGEsTG\nxoq0lBsYGAigegK0e/duvi2PPB4PCQkJMDExEdn5RM2CBQtw69YtXLhwga95ffDgwVi6dCmrSUtZ\nWRlmzpyJsLAwZklBTk4OkyZNwpYtW+rl27V582ah8/ivIy7toRo+fPiAfv36sY7zMR9P5LlcrlCW\nKF+DOK0etLS0MGvWLMyaNQvXr18XyzlEjWzSIiW8e/cOO3fuRExMTKM1spJ2Pl7Pbmx8TixQGGr6\nbIgIQUFBfN4vioqKaN++PYKCguodt2fPnjh//jy0tLTQo0ePz0602FwoT5w4gcOHD6NPnz585zAz\nM0NeXp7QcQHAy8sL8fHxiIyMZJyHExMT4eHhgblz5zI6P19DQ/UPNUbEvZtKXDeDtRu0RUVsbCxm\nzpyJ5ORkgaXeV69eoV+/fggKCsJ3330n8nMDaBRLQ4Bs0iI1fM7Iis3ddX5+vkgaN2VIjrKyMsyb\nNw8nTpxARUUFBg8ejMDAQDRv3pxV3JpGVltbW2aHkygYMWIEc1H/2LxOlDx79kxgSQuo3r7NtiJ1\n7NgxHD16lG+i6OTkBGVlZYwbN65ekxageqnN398fS5YsqfMHaeXKlfD29karVq1Y5d3YGD58OA4f\nPozVq1eDw+FgyZIl6NmzJyIjIzFkyBDW8cV5MxgeHo7169czSsampqaYN28efvjhB6Hibd68GdOn\nT6+zN63GMNff319sk5bGgqyn5T+OnJwc+vfvDzc3N4wdO1bkOgiNlX379iEoKAj5+fm4fPky2rVr\nh82bN8PAwEBor52cnBx06NBBxJlWS4Nv374dEydOhJKSEg4ePIiBAwfiyJEjIj9XY2LAgAEYO3Ys\nZs2aBXV1daSlpcHAwAAzZ85Ebm4uq23JKioquHbtGkxNTfnG79y5A0tLS5SWltYrnre3N16/fo2d\nO3fWeXzGjBlo2rQp1q5dK3TOMgSxtbX95DEOhyO0jcSWLVvg4+MDd3d3WFtbg4iQlJSE3bt3Y/36\n9Z/0fPsc7dq1Q1RUlMBnrobMzEwMHTqU9e6kRk+DStnJaHDS09PJy8uLWrZsSU2bNiV3d3e6cuWK\nSGI3hDuwONi+fTs1b96cVq5cScrKyowqaUhICA0cOFDouBwOh3R1dWnChAkUFBQkMjdjQ0NDOnjw\nIPP8ypUrJC8vT5WVlULH9PLyordv3zL//txDWklKSiJ1dXWaMWMGKSkpkaenJw0ePJhUVVUpNTWV\nVWw7Ozv64YcfqLy8nBkrKyujH374gQYNGlTveJ07d6aLFy9+8nhSUhLj5v4tUVRURPfv32eeX7ly\nhTw9PWnHjh0SzOrLGBoa1unKvWvXLjI0NBQqZpMmTT6r0puTk0NKSkpCxf4vIau0SJDRo0dj7969\n0NDQYEStPgUbPQugWgE3MjISe/fuxZkzZ9ChQwe4ubnBxcVFqB0RgPjdgfPy8hASEoK8vDwEBASg\nZcuWiIqKgp6eHqM0KwxmZmZYvXo1Ro4cybdj4fbt2xg4cKDQ6rVPnjxBbGws4uPjceHCBWRnZ6NV\nq1YYMGAABg4cyGeQVx8UFRWRn5+PNm3aMGPKysrIzs4WepeCra0tjh8/Dk1NTbHdjQLi3zmTnp6O\nDRs28Am1+fr6omvXrvWOVZvbt2/DwcEB7969Q7du3cDhcHDz5k0oKSnh7Nmz9f78qaqqIiMj45MN\nlUVFRTA1Na13Baex891338Hd3R0uLi4oLi5Gx44d0aVLF2RnZ8PDwwNLliyRdIp10qRJE9y5c0dA\n7Tk3NxddunTBu3fv6h3TyMgIGzZswKhRo+o8HhERAW9vb6FEE/9LyCYtEmTKlCkIDAyEurp6g+hZ\nANWW6tu3b8eCBQvw4cMHKCgoYPz48Vi7di1jKPa1qKuri80dOD4+Ho6OjrC2tkZCQgIyMjJgaGiI\ndevWISUlBUePHhU69qe2Webk5MDc3FxkW3xzc3OxcuVKHDhwAFVVVULvVpKTk0NxcTHf5LL2cog0\n4+/vj5UrV8Le3h59+/YFUG1SefbsWSxevBjNmjVjXittDavl5eXYv38/n/z7xIkT+QTnvpbmzZsj\nIiIC/fv3r/N4QkICRo8ezdruobGhpaWF5ORkdOrUCYGBgTh8+DCSkpIQHR2NGTNmCK1qLO6bQTMz\nM0yZMkXA1XndunUIDQ0VShF31qxZuHDhAq5evSqwjF9eXg5LS0vY2toyu/6E4cmTJ/D29mbE9j7+\n+W8MOypljbgSpPZERFSTkk+RmpqK4OBgHDp0CKqqqvD29oabmxsePXqEJUuWYMSIEUhJSalXTHG6\nA8+fPx8rV67EnDlzoK6uzozb2toiICCAVWwDAwPcvHlTYJvlmTNnWMlZv337FomJibhw4QLi4+Nx\n8+ZNmJqaYtasWRgwYIDQcYkIrq6ufDsW3r17hxkzZvCJnwl7AT537hxsbGyE+jH+EklJSfDz88PM\nmTOZMQ8PD2zduhUxMTE4ceIEq/hVVVXIzc2tU+30UxOEr0VZWZm1+m0NVlZW2Ldv3ydzCgsLY+U6\n3FipqKhgPtcxMTH4/vvvAQAmJiZ4/PixUDGbNm3KVPdqFI5FzZIlS/C///0PSUlJsLa2BofDQWJi\nIk6dOoUDBw4IFXPRokWIiIhAx44dMXPmTHTq1AkcDgcZGRnYtm0beDweFi5cyCpvV1dXFBUVYfHi\nxSJRXpcEskrLfxx/f3+EhIQgKysLTk5OmDZtGpycnPjEkXJzc2FiYlJvE8Xo6Ghs3LgRO3bsQPv2\n7UWat5qaGtLT02FgYMBXDSkoKICJiYlQ5dcaQkJCsHjxYmzcuBFubm7YvXs38vLy8Mcff2D37t34\n8ccfhYqroKCAZs2awcXFBba2trCxsRHJRfNLVbgahJ34amho4P379+jVqxezlGVtbS0Sq3o1NTXc\nvHlToIyek5ODHj16sBIPS05Oxk8//YTCwkKBybOwOjwJCQlf9br6Toji4uIwZMgQzJ49G/PmzWN2\nCT158gTr1q1DQEAAoqOjYWdnV++cGzNWVlawtbWFs7Mz44/TrVs3JCcnY+zYsXjw4IGkU/wkly5d\ngr+/PzIyMphKnLe3N/r06SN0zMLCQvzyyy84e/Ys85nmcDiwt7fH9u3bWV9nxVkdbzAk0kkjQwBx\nNbUaGxvT6tWr6fHjx598zfv372nv3r31jq2pqUmKiorE5XJJTU2NtLS0+B5saNOmDSUlJRERkZqa\nGtMsGxERIXSjW2127txJ+vr6xOFwiMPhUNu2betsrKsPI0aMIG1tbWrZsiWNGzeOtm/fTnfv3mWd\nq7iprKykS5cu0R9//EH29vakrq5OCgoKZGVlRb6+vqxi6+vr07p16wTG161bR/r6+qxid+vWjX74\n4Qe6e/cuvXjxgl6+fMn3EAYOh8N852o+Gx8/hP0+BgUFUZMmTYjL5ZKmpiZpaWkRl8ulJk2a0Pbt\n24WK2diJi4sjTU1N4nK5NGXKFGZ8wYIFNGrUKAlm9mkqKiro0KFD9OTJE7Gd4/nz55SSkkJXrlyh\n58+fiyyuqakpXb9+XWTxJIGs0iIliLupVRx8ySmYTY+Cj48PLl++jCNHjqBjx464fv06njx5gkmT\nJmHSpEkiM4T8999/UVVVVafeh7CkpaUhPj4e8fHxuHjxIjgcDgYOHIhDhw6J7Bzi5Pbt29iwYQPr\nXhwA2Lt3L9zc3ODg4MD0tCQnJyMqKgq7d++Gq6ur0LFVVVVx69YtgSoOG7S1taGurg5XV1e4uLh8\nUgtH2Araw4cPER4ejtzcXBAROnbsiLFjx6Jt27Zs0m7U8Hg8vH79mk8nqKCgACoqKqy/l+Lq4ajd\nF9eYEGd1vKGQTVqkBHGW7V6+fImUlJQ61/0nTZok8vOJgoqKCri6uuLQoUMgIsjLy4PH4+Gnn37C\n3r17+dRb60t5eTmIiJFiLywsxPHjx2FmZoahQ4eKJP8bN24gLi4OcXFxiIqKAofDwYcPH0QSW9Rk\nZGQwO57i4+PB4/FgY2ODgQMHYsCAAaz9Tq5cuYLAwEC+MrqHhwesrKxYxbWzs4OPjw+fhD9bPnz4\ngOPHjyM4OBgXL16Ek5MTM+lqjOv/jQVReDzVhbhuBvv374958+Zh+PDhokizwdDS0kJZWRkqKyuh\noqIiILbXGLyvZJMWKcHMzAwHDhwQid9GbSIjIzFx4kSUlpZCXV2d70vL4XDq/SF9/fo1o9j4+vXr\nz75WWNfh2uTl5eHGjRuoqqpCjx49RCLeNnToUIwePRozZszAy5cv0alTJygqKuLff/+Fv78/fvnl\nF6Hibtq0CRcuXMDFixfx5s0bdO/enekR6d+/v0jeD3HA5XLRokULzJ49G99//z2r7eTiJi0tjfl3\nXl4eFi1ahHnz5qFr164CF2Bzc3NW57p//z5CQkIQGhqK9+/fY/LkyVi+fLnInKRlVKsXz5o1SyQe\nT3UhrpvB48ePY/78+Zg3b16djusdO3YU6flEhTir4w2GhJalZHzE2bNnaejQoZSfny/SuB06dCBP\nT08qLS0VSTwul8us5dZe/6/9YLPu3xBoa2vT7du3iahaDMrc3Jx4PB6Fh4eTiYmJ0HF79epFc+fO\npcjISHr16pWo0hU7np6e1KNHD1JUVCRLS0vy8fGh06dP05s3b4SKV/tvf/Xq1Wcf9aXms/W5fhNR\nf/7u3btHtra2xOVyqaSkRGRxZRC5u7uToaEhnT59mvlMnDp1ioyMjGjGjBms44urh6Ouz11juPb9\nF5BVWiTIx8JbpaWlIi/bqaqqIj09HYaGhqxyrSE+Ph7W1taQl5dHfHz8Z18rzDZfPz+/r3odG9Ep\nFRUVZGZmQl9fH+PGjUPnzp2xdOlS3L9/H506dUJZWZnQsRszL1++xMWLF5l+nPT0dHTv3h3Jycn1\niiMnJ4fHjx+jZcuW4HK5dS6rkJBO24WFhV/9Wjb9Bu/fv8exY8cQHByMy5cvw9nZGVOnThXpUpSM\nav2ajz2egOrdVuPGjcOzZ89YxRdXD0dWVtZnj3fq1Elk5xIX5eXlqKio4BuT1mpwbWR1TgnSEJb1\n9vb2SE1NFdmkpfZEhI32yKdYtmwZdHV10bJly09qwNQYqwmLsbExTpw4gVGjRuHs2bPw8vICADx9\n+pT1l/bly5fYs2cPMjIywOFwYGpqCjc3N7HpRYiSqqoqVFZW4sOHD3j//j0qKipQUFBQ7zixsbGM\naFxcXJxIc6w9EUlISEC/fv0ElmsqKytx6dIloSYtKSkpCAkJwaFDh2BgYABXV1eEh4fzieDJEB1l\nZWV1mkS2bNlS6JuHum4GjYyMRHIzOHXqVAQEBDSKSUldlJaWwtfXF+Hh4SgpKRE43hjE5WSVlv8g\nf//9N/PvZ8+ewc/PD1OmTKlz3b9GzElacHJyQlxcHOzt7TF16lQ4Ozuzarqti6NHj+Knn34Cj8fD\noEGDEB0dDQD4448/kJCQgDNnzggVNzU1Ffb29lBWVoalpSWICKmpqSgvL0d0dLTUWr97enriwoUL\nuHPnDpo1a4b+/ftj4MCBGDhwILp06SK28968eZNVr0Htik5tSkpK0LJlS6EuwFwuF/r6+pg8eTJ6\n9er1yddJ2/emsTJo0CBoa2sjLCyMUYEtLy/H5MmT8fz5c8TExNQ75pf6NmpT3x6OT33mGgu//fYb\n4uLi4Ofnh0mTJmHbtm14+PAhduzYgTVr1mDixImSTvHLSHBpSkYtrl27RmlpaczzEydO0IgRI2jB\nggX0/v37esX61Hq/qPQmxM2jR49o9erV1LFjR9LR0SEfHx+RmQ/W8PjxY7p+/TrxeDxm7MqVK5SR\nkSF0TBsbG3J1daWKigpmrKKigiZPnkzfffcdq3zFyZgxY2jLli2Unp4u9nO9fPmStm3bRj169GD9\n+eNwOPT06VOB8aysLFJXVxc6pji/NzX6LB8/mjVrRrq6utS/f38KDg4WOn5jIz09ndq0aUPa2tpk\nZ2dHgwYNIm1tbWrTpg3TdyZNcDgcseqziBs9PT2Ki4sjIiJ1dXXGoDEsLIwcHR0lmNnXI6u0SAm9\ne/fG/PnzMWbMGNy7dw9mZmYYPXo0rl69Cmdn5wZZSpJGEhISEBISgmPHjqFr166IiYkRi9y8KFBW\nVsaNGzdgYmLCN3737l1YWFh8s70yQPWSUXBwMCIiItCuXTuMGTMGY8aMEWq3XI2fzMmTJ+Hg4MBn\nb8Dj8ZCWloZOnTohKipKZPmLik2bNmHVqlVwdHRkqnFXr15FVFQUvLy8kJ+fj3379mHLli0isxCQ\ndkTp8fQxp0+fhpycHOzt7fnGo6OjwePx4OjoWK94XC4XT548EdmW7IZGTU0Nd+7cQbt27dC2bVtE\nRETA0tIS+fn56Nq1KyuF6oZC1tMiJWRnZzOl8iNHjmDAgAH466+/kJSUhB9//FHoSUtYWBjGjx/P\nd2EHqvUoDh06JLU6LTX07t0bBQUFuHv3Lm7cuIGKigqhLmZfMk6rjbAePhoaGigqKhKYtNy/f5/P\nP+lb4cGDB9i7dy+Cg4NRWlqKcePGoaKiAseOHWPl8VTTH0REUFdX5/s8KCoqok+fPlL7g5+YmIiV\nK1cKOH7v2LED0dHROHbsGMzNzREYGCi1f4OoEaXH08fMnz8fa9asERivqqrC/Pnz6z1pAaq3M39J\ns0da9U5qrFDatWsHMzMzhIeHw9LSEpGRkdDU1JR0el+FrNIiJWhoaODatWvo0KEDhgwZgmHDhsHT\n0xNFRUXo1KmT0M7D4lj3r2HZsmWYMmWKWFQhL1++jODgYISHh6Njx46YMmUKfvrpJ6G/WF/r3wMI\n7+Hj4eGB48ePY8OGDejXrx9jojZv3jyMGTPmm6qWOTk5ITExEcOGDcPEiRPh4OAAOTk5KCgo4Nat\nW6wmLTUsX74c3t7eAhoZ0synvJhyc3PRvXt3vH37Fnl5eTA3N0dpaamEshQvtXvuvgTb3iFlZWVk\nZGQI7BwqKChA586d6/0ec7lcbN68+YuN9dKqd7Jp0ybIycnBw8MDcXFxcHZ2Bo/HQ2VlJfz9/eHp\n6SnpFL+MBJemZNTC1taWJk2aRGFhYaSgoMCsNV64cIHatWsndNxPrfvfvHmTtT9Qz549SU5Ojuzs\n7OjAgQNUXl7OKh4R0dq1a8nExIRatGhBs2fP5uvzkXbev39PHh4ejB9Tja/M7Nmz6d27d5JOr0GR\nk5MjLy8vys7O5huXl5enO3fuSCgryaOnp0f+/v4C4/7+/qSnp0dERLdu3aJWrVo1dGoNRkP23LVq\n1YrOnz8vMH7u3Dlq0aKFULk35p6WjyksLKRjx47RzZs3JZ3KVyOrtEgJaWlpmDhxIoqKijBnzhzG\nW2fWrFkoKSnBX3/9Va94PXr0AIfDwa1bt9C5c2e+baE8Hg/5+flwcHBAeHg467xDQkLw119/4cOH\nD/jxxx8xdepU9O7dW6h4Nbs3hg0bBkVFxU++zt/fv96xnz59+tmu/8rKSly/fh2Wlpb1jl2bsrIy\n5OXlgYhgbGzMWtWzMVK7UmZiYgIXFxeMHz8eurq6Iqu0ANU7wcLDw1FUVCRgk3D9+nWRnEOU7Nq1\nC7/88gucnJxgaWkJDoeDlJQUnD59GkFBQXBzc8PGjRuRkpKCw4cPSzrdRo+7uzuSk5Nx/PhxGBkZ\nAaiuao0ZMwa9e/fG7t276xWvse8e+i8gm7RIOe/evWPK6vVh+fLlzH/nzp0LNTU15piioiLat2+P\nMWPGfHZiUB8qKysRGRmJkJAQREVFoVOnTpg2bRpcXV3rpVEycODAL64XczgcxMbG1jvHjy84pqam\nOHv2LPT19QFUm6vp6uo2Cq2CxkJZWRkOHTqE4OBgpKSkgMfjwd/fH1OnTmXd5xMYGIiFCxdi8uTJ\n2LVrF6ZMmYK8vDxcvXoVv/32G1atWiWiv0K0JCUlYevWrcjKygIRwcTEBLNmzUK/fv0kndp/jlev\nXsHBwQGpqamMKeWDBw/w3XffISIiot7LzVwuF8XFxY160pKSkoILFy7U6UUnzM1gQyObtPzHCQ0N\nxfjx4xkNBHFR22guNjYW/fr1w5MnT/Do0SPs2rUL48ePF+v5v4aPLzjq6uq4desWI7z35MkTtG7d\nWuCL/DkaosFX3PB4PGzatOmTFQtRNRVmZWVhz5492LdvH16+fIkhQ4bUq7/hY0xMTLB06VJMmDCB\n7//lkiVL8Pz5c2zdupVVvi9fvsTRo0eRl5eHefPmoVmzZrh+/TpatWqFNm3asIr9rRMbG4uZM2ci\nOTlZQNDx1atX6NevH/7880/079+f9bmICOfOncOtW7egrKwMc3NzkcRtjKxevRqLFi1Cp06d0KpV\nKwEvOmFuBhsciS1MyeCjsrKS1q9fT71796ZWrVoJ6DiwJTU1lfbt20f79+8XqRdHamoq/fbbb9Ss\nWTNq3bo1+fr6Mv04REQbNmygli1biux8bPh4PVpNTY3y8vKY58XFxfVeR3d1dWUekydPJg0NDdLT\n06NRo0bRqFGjSF9fnzQ0NMjV1VVkf4eoWbx4MbVu3ZrWr19PSkpKtGLFCnJzcyNtbW0KCAgQ+fkq\nKyvp+PHjNHz4cFZxlJWVqaCggIiIWrRowazLZ2dnU7NmzVjFvnXrFrVo0YKMjY1JXl6e+ZwsWrSI\nXFxcWMXm8XiUlZVFFy9epPj4eL7Ht8Lw4cPr7O2pISAggEaOHNmAGX0btGzZkkJCQiSdBitkkxYp\nQVw/HE+ePCFbW1vicDikpaVFmpqaxOFwyM7Ors4G3frQtWtXkpeXJycnJzp+/DhVVlYKvObp06fE\n4XBYnUdUiGPSUhsfHx+aNm0a3/tQWVlJ7u7u5O3tLXRccWNoaEj//PMPEVW/J7m5uURU/cMxYcIE\nSab2WQwMDOjatWtERGRhYUFBQUFEVG0+ynaiP2jQIJo3bx4R8X9OkpKSWDXGX758mQwMDOo0fZRW\nsUdxoK+vT3fv3v3k8YyMDKYxWRiSk5Pp9OnTfGOhoaHUvn17atGiBU2fPv2ba44nItLR0RFojm9s\nyCYtUoK4fjjGjRtHvXr14rtA3LlzhywsLOjHH39klbOfnx89ePCAVYyGhMvlUm5uLr169YpevnxJ\n6urqdOvWLcZdNjs7m9UPR/PmzetU7s3MzGR95y9OVFRUqLCwkIiqL2o1E4G8vDzS0NCQZGqfxc3N\njZYtW0ZERH/++ScpKyvT4MGDSVNTk6ZOncoqtoaGBvMdrD1pKSgooCZNmggdt1u3bvTDDz/Q3bt3\n6cWLF/Ty5Uu+x7dCkyZN+CqyH5OTk0NKSkpCx3dwcKA1a9Ywz9PS0kheXp6mTZtGGzduJB0dHVq6\ndKnQ8Rsra9euJU9PT0mnwQqZuJyUUFxcjK5duwKo1nJ49eoVAGDYsGFYvHix0HGjoqIQExMDU1NT\nZszMzAzbtm3D0KFDWeXMJi9JQETo2LEj3/Paiqz0f87DwlJZWYmMjAwBM7WMjIx69ck0NG3btsXj\nx4+hr68PY2Njxifp6tWrAqKE0sTOnTuZ93XGjBlo1qwZEhMTMXz4cAHxtvqipKSE169fC4xnZWWx\nUkPNycnB0aNHBXRavjXatGmD9PT0T74PaWlpaN26tdDxb968iRUrVjDPDx06BCsrK+zatQsAoKen\nh6VLl2LZsmVCn6Mx4u3tDWdnZxgZGcHMzExgg4e09t3VRjZpkRLE9cNRVVVV584jBQUFkfyQPnjw\nAH///XedDZzS1okuasfhj5kyZQqmTp2K3Nxc9OnTBwCQnJyMNWvW1EvcrqEZNWoUzp8/DysrK3h6\nemLChAnYs2cPioqKGAdsaYTL5YLL5TLPx40bh3Hjxokk9ogRI+Dn58dIAnA4HBQVFTFWG8JiZWWF\n3Nzcb37S4uTkhCVLlsDR0VFgk0B5eTmWLl2KYcOGCR3/xYsXfO7R8fHxcHBwYJ737t0b9+/fFzr+\npxrIORwOlJSUYGxsDAMDA6Hji4tZs2YhLi4Otra20NbWZnWTJjEkXOmR8X/4+vrSqlWriIjoyJEj\nJC8vT8bGxqSoqEi+vr5Cx/3++++pf//+9PDhQ2bswYMHNGDAANaNbjExMaSiokKdO3cmeXl56t69\nO2lqalLTpk3J1taWVWwiooSEBJo4cSL16dOHWYYKCwujixcvso4tDng8Hq1du5Z0dXWZPgVdXV1a\nu3Ztnf0+0kpycjJt3LiRTp48KelU6qS0tJR+/fVX0tXVpRYtWtCECRPo2bNnIj3Hq1evyNramjQ1\nNUlOTo709PRIQUGB+vfvT2/fvhU6bkREBJmZmVFISAilpqbSrVu3+B7fCsXFxaSrq0t6enq0du1a\nOnHiBJ08eZLWrFlDenp6pKurS8XFxULH19fXZxqb379/T8rKyhQTE8McT0tLY9X3VNODVFdfUs1/\n+/fvT8+fPxf6HOJATU2NaUNorMgmLVKKqH44ioqKqEePHqSgoECGhoZkZGRECgoK1LNnT7p//z6r\n2L1796bFixcT0f9f93/z5g19//33tH37dlaxjx49SsrKyjRt2jRq0qQJ01Owbdu2RuFGWtMn0xiI\nj4/nc6auoaKiQip3tHh7e5OKigpNnz6dZs2aRc2bN6exY8eK5Vznz5+n9evX09q1a+ncuXOs431K\n+fVba8Qlqu4PcnR05Pvx53K55OjoSPn5+axiu7u7U9++fSkhIYHmzJlD2tra9P79e+b4/v37ycLC\nQuj4MTExZGVlRTExMfT69Wt6/fo1xcTEUJ8+fejUqVOUmJhInTt3Zt1bJWr09fVZOdlLA7JJi4Qp\nLS1tkPNER0dTYGAgBQQEiOTiS8TfMKypqclYyd+8eZPVDgsiou7du1NoaChznppJy40bN/7T+UZq\nlQAAIABJREFUEueSgMvl1ilN/u+//0rlD6mhoSEdPHiQeX7lyhWSl5dvFNWsgoKCzz6+RZ4/f04p\nKSl05coVkVUmnj59SjY2NsThcEhdXZ0iIiL4jtvZ2dHvv/8udPzOnTtTUlKSwHhiYiKZmZkRUbVV\nAJsdUOIgODiYxo0b12C/O+JA1tMiYTQ1NWFlZQVbW1vY2tqiX79+Imt+rKiowNChQ7Fjxw4MGTIE\nQ4YMEUncGlRVVfH+/XsAgK6uLvLy8tC5c2cAwL///ssqdlZWVp0CUBoaGnj58iWr2OKkscnKA59u\nQC4pKZFKM8L79+/ju+++Y55bWlpCXl4ejx49gp6ensjOIw7lUHGYizZ2tLS0hLb9+BQtWrTAxYsX\n8erVK6ipqUFOTo7v+JEjR/hUwutLXl6egCgeUH19unfvHgCgQ4cOrK+DoiYwMBB5eXlo1aoV2rdv\nL9DvKK3XqNrIJi0SZs+ePYiPj8dff/2FlStXQklJCX369GEmMVZWVvWW8K9BQUEBt2/fFluzVZ8+\nfZCUlAQzMzM4Oztj7ty5SE9PR0REBNOIKiytW7dGbm6ugDtrYmIio2ArbdSWlT958qSArLy0UaPm\ny+Fw4OrqyjdZ5vF4SEtLk0ppeR6PJ2A/IS8vj8rKSpGd40vKoWzIy8vD5s2bkZGRAQ6HA1NTU3h6\nejLeODJEx6csRJo1a8Yqbq9evTBv3jyEhYUxu8mePXsGHx8fZgKWk5PDWAdICyNHjpR0CqyRyfhL\nEQ8ePEBsbCzi4+MRFxeHwsJCKCsrw9raGmfPnhUq5ty5c6GgoIA1a9aIOFvg3r17ePv2LczNzVFW\nVgZvb28kJibC2NgYmzZtYnVXuW7dOoSGhiI4OBhDhgzB6dOnUVhYCC8vLyxZsgQzZ85knX9ubi7y\n8vLQv39/KCsrs97yLG5ZeVFTs6MpNDQU48aNg7KyMnOsxp9q+vTpaN68uaRSrBMulwtHR0e+SVZk\nZCTs7Oz4KkNstm+2atUKa9euhaurK5tUBTh79iy+//57dO/eHdbW1iAiXLp0Cbdu3UJkZKTIq6Ey\nxENWVhZGjBiB/Px86OnpMbvLDA0NcfLkSXTs2BEnTpzAmzdv4OLiIul0/1PIJi1SSk5ODsLCwhAY\nGIi3b98KbeI3a9YshIWFwdjYGBYWFgLlfmnbllybhQsXYtOmTXj37h0AoEmTJvD29ubTXxCGkpIS\njB8/HrGxseBwOMjJyYGhoSHc3NygqamJjRs3ChVXRUUFGRkZaNeuHVq2bIlz586hW7duyMnJQZ8+\nfVBSUsIqb3GxfPlyeHt7S+VSUF187fbxkJAQoc/RunVrJCQkoEOHDkLHqIsePXrA3t5e4CZi/vz5\niI6ObhTleRnVEBHOnj2L7OxsxvhyyJAhfNvwZYge2aRFSrh37x7i4uJw4cIFXLhwgTEN69+/PwYM\nGABra2uh4tra2n7yGFuDLCLCtWvXUFBQAA6HAwMDA/To0UOky1FlZWW4e/cuqqqqYGZmxmoduoZJ\nkybh6dOn2L17N0xNTZmKSHR0NLy8vHDnzh2h4hoaGuLo0aPo2bMnevfujWnTpuHnn39GdHQ0fvzx\nR5EZD8oQP+vWrcOjR4+wefNmkcZVUlJCenq6wGQoOzsb5ubmzARdhgxRoaWl9dXX5MZwjZL1tEiY\nyZMnIy4uDm/evIG1tTX69++PmTNnwsLCQqB5TBjEJagWFxcHNzc3FBYWombeWzNxCQ4OFpmLqoqK\nCiwsLEQSq4bo6GicPXtWYL25Q4cOKCwsFDqunZ0dIiMj0bNnT7i5ucHLywtHjx5FampqvdygG5on\nT57A29sb58+fx9OnT/HxfYywVb7GjLiUQ1u0aIGbN28KTFpu3rzJuI/LaBycP3+e+c583KgdHBws\noawEqT3xLikpwcqVK2Fvb4++ffsCAC5fvoyzZ882GoVz2aRFwuzbtw/6+vr4/fffMWjQIJFXKmrz\n4MEDcDgctGnThlWc3NxcDBs2DFZWVti0aRNMTExARLh79y4CAwPh5OSEtLS0ejfM1ueHnU2/Qmlp\nKVRUVATG//33X1Y7t8QpKy9OXF1dUVRUhMWLF6N169aNUyVTxIhLOXT69Olwd3fHvXv30K9fP3A4\nHCQmJmLt2rWYO3euSM4hQ/wsX74cfn5+sLCwkPrvzOTJk5l/jxkzBn5+fnw9gR4eHti6dStiYmKk\nWgGbQQLbrGXUIiMjg/78808aP3486ejokKamJg0bNozWr19PV69eJR6Pxyo+j8ej5cuXk4aGBnG5\nXOJyudS0aVPy8/MTOvZvv/1GdnZ2dR6rqqoiOzs7mjlzZr3jurq6Mo/JkyeThoYG6enp0ahRo2jU\nqFGkr69PGhoa5OrqKlTeNTg5OdGiRYuIqFoD5t69e8Tj8eiHH36gMWPGsIrdGFFTU6MbN25IOg2p\nQlzKoVVVVeTv709t2rRhBNXatGlDmzdvpqqqKpGfT4Z40NHRobCwMEmnUW9UVVXrNKrMzs4mVVVV\nCWRUf2SVFgljYmICExMT5k787t27zO6hjRs3ory8HDY2Nvjnn3+Eir9w4ULs2bMHa9asYXYrJCUl\nYdmyZXj37h1WrVpV75gXLlzAH3/8UecxDoeD2bNnY8GCBfWOW7tx0tfXF+PGjUNQUBCzTMbj8fDr\nr7/WqY9QH9avX4+BAwciNTUVHz58gI+PD+7cuYPnz58jKSmJVeyXL18iJSWlzpLxpEmTWMUWF3p6\negJLQt86zZo1E/kWZCJCUVERZsyYAS8vL7x58wYAoK6uLtLzyBA/Hz58kEo5gC+hra2N48ePY968\neXzjJ06cgLa2toSyqicSnjTJqIPHjx/TwYMHyd3dnamQCEvr1q3rtAI4ceIE6erqChVTXV39szLb\n9+7dIzU1NaFi19C8eXPKzMwUGM/MzKRmzZqxik1U/R4vWbKEnJ2dydHRkRYuXEiPHj1iFfPvv/8m\ndXV1ppqlqanJPNj4nIibs2fP0tChQ1lLp/+XEIdyKI/HIwUFBcrOzhZZTBmSwcfHh/z8/CSdRr0J\nCQkhLpdLTk5OtGLFClqxYgU5OzuTnJwchYSESDq9r0JWaZECnj59igsXLjC7h7Kzs6GoqAhLS0t4\neXl9dgfQl3j+/DlMTEwExk1MTITuFH/79m2dPSE1qKiooKysTKjYNVRWViIjIwOdOnXiG8/IyBCJ\nO7WOjg6WL1/OOk5t5s6di6lTp2L16tWffX+kjfHjx6OsrAxGRkZQUVERaDptDDsKRI04lEO5XC46\ndOiAkpISkW+lltGwvHv3Djt37kRMTAzMzc0FPh/SKiXh6uoKU1NTBAYGIiIiAkQEMzMzJCUlwcrK\nStLpfRWySYuEMTMzQ1ZWFuTl5dG7d2+MGTMGtra2sLa2FrBsF4Zu3bph69atCAwM5BvfunUrunXr\nJnTcu3fvori4uM5jopCunjJlCqZOnYrc3FxGXTc5ORlr1qz5ap2OzyGOZZyHDx/Cw8OjUU1YAIh8\nW+9/AXEph65btw7z5s3Dn3/+iS5duojlHDLET1paGrp37w4AuH37Nt8xaW3KraysxIEDB2Bvb48D\nBw5IOh2hkem0SJgFCxbA1tYWNjY2Yvmxi4+Ph7OzM/T19dG3b19wOBxcunQJ9+/fx+nTp/k8XL4W\nLpcLDodTZx9EzTiHw2G1VbaqqgobNmxAQEAAHj9+DKBa8MvT0xNz585ltR08MjISEydORGlpKdTV\n1QUk2oWtLIwePRo//vgjxo0bJ3RuMv7baGlpoaysDJWVlVBUVORTIQa+zaqWjIajtgBmY0U2afkG\nePjwIbZv347MzEymHPjrr79CV1dXqHhfq2Uiqi/G69evAYB1A24NHTt2hJOTk0iWcf7++2/m38+e\nPYOfnx+mTJmCrl27CpSMv//+e1bnagjKy8tRUVHBNyaq970xcu3aNcYjyMzMDD169GAVb+/evZ+9\nE6+9PVVG40BUUhINga2tLTw9PRu1B5Fs0iLjm0NVVRXp6ekiMV78WslutpUncVJaWgpfX1+Eh4fX\naTUgrXmLk6dPn+LHH3/EhQsXoKmpCSLCq1evYGtri0OHDjEmeTK+TaqqqrBy5Ups3LgRb9++BVC9\nC2zu3LlYuHCh1Er5HzlyBPPnz4eXlxd69eolYN1hbm4uocy+HllPy3+cnJwcnDx5kpHaNzQ0xMiR\nI2FgYCDp1L7I0aNHER4ejqKiInz48IHvGBuPFnt7e6Smpopk0iKKpmBJ4+Pjg7i4OGzfvh2TJk3C\ntm3b8PDhQ+zYsUMsRpuNgVmzZuH169e4c+cOTE1NAVT3cU2ePBkeHh44ePCgUHHl5OTw+PFjAfXb\nkpIStGzZ8pucIDZGxCEl0RCMHz8eQLWgXA2iWtJvMCSyZ0lGg7B69WqSl5cnLpdLOjo61KpVK+Jy\nuaSgoEDr16+XdHqfJSAggNTU1Oi3334jRUVF+vnnn2nw4MHUtGlT+v3331nF3r17N+nr69PSpUvp\n6NGjdPLkSb7Ht4aenh7FxcURUfV29hrxqbCwMHJ0dJRgZpJDQ0ODUlJSBMavXLlCTZs2FTouh8Oh\nJ0+eCIw/fPiQlJSUhI4ro2ERh5REQ1BQUPDZR2NAVmmREoqKihiL89oQEe7fvw99ff16xYuLi8Oi\nRYuwePFieHp6QktLC0B1o9/mzZsxf/58WFpaiswjSNRs374dO3fuxIQJExAaGgofHx8YGhpiyZIl\nrJsVp0+fDgDw8/MTOCbM3caVK1fw/PlzODo6MmNhYWFYunQpSktLMXLkSGzZsoWVRYA4ef78OVN5\n09DQYN5fGxsb/PLLL5JMTWJUVVUJ9CQBgIKCglDVtZrdexwOB7t37+Yz/uTxeEhISKhTmkCGdCIO\nKYmGoDE34NYg62mREkRdNh4/fjw0NTWxY8eOOo+7u7vjzZs3Qpe5xU3tLveWLVvi3Llz6NatG3Jy\nctCnT586ey8khaOjIwYOHAhfX18AQHp6Onr27MloIqxfvx4///wzli1bJtlEP4G5uTm2bNmCAQMG\nYOjQoTA3N8eGDRsQGBiIdevW4cGDB5JOscEZMWIEXr58iYMHDzIN6w8fPsTEiROhpaWF48eP1yte\nzaSwsLAQbdu25dv9pqioiPbt28PPz6/RaGV861hZWcHKykpASmLWrFm4evUqkpOTJZTZ13H37t06\nl90bw2YB2fKQlMDhcOjp06cC4wUFBaSiolLveO3bt6eLFy9+8nhCQgK1b9++3nFrY2trSy9evBAY\nf/XqFdna2rKKbWBgQNeuXSMiIgsLCwoKCiKiavVWaVOX1dHRoatXrzLPf//9d7K2tmaeh4eHk6mp\nqSRS+yr8/f0pICCAiIhiY2NJWVmZFBUVicvl0ubNmyWcnWQoKiqiHj16kIKCAhkaGpKRkREpKChQ\nz5496f79+0LHHThwID1//lyEmcqQBBcuXCBVVVUyNTWlqVOnkpubG5mampKamholJCRIOr1PkpeX\nR+bm5sThcIjL5TL+VzW+dI0BWaVFwsyZMwcAEBAQgOnTp/NtweXxeLhy5Qrk5OTq7YmjoqKC7Oxs\ntG3bts7jDx48QIcOHVBeXi507lwuF8XFxQLVoadPn6JNmzYCW2frw7Rp06Cnp4elS5ciKCgIc+bM\ngbW1NVJTUzF69Gjs2bNH6NhAtX7Nhg0bmO2spqammDdvnlC6NUpKSsjJyYGenh6A6mUVBwcHLFq0\nCABQUFCArl27Ml4z0k5hYSGuXbsGIyMjVgKE/wXOnTvHJxUwePBgkcavrKzEu3fv+JaLZDQOHj16\nhG3btolMSqIhGD58OOTk5LBr1y4YGhoiJSUFJSUlmDt3LjZs2CDU9a+hkfW0SJgbN24AqO5dSU9P\nh6KiInNMUVER3bp1g7e3d73jvnv3ji/WxygoKAiUBr+WtLQ05t8fK+PyeDxERUWx1izYuXMn0zsw\nY8YMNGvWDImJiRg+fDhjLiks+/fvx5QpUzB69Gh4eHiAiHDp0iUMGjQIe/fuxU8//VSveK1atUJ+\nfj709PTw4cMHXL9+nc8i4M2bN3X2R0gr7dq1+0+sfYuCIUOGYMiQIazjnD59GiUlJXBxcWHGVq1a\nhRUrVqCyshJ2dnY4fPgw03smQ3qprKzEqlWrMHXqVKndJfQpLl++jNjYWLRo0QJcLhdcLhc2Njb4\n448/4OHhwfweSTWSLPPI+P9MnjyZXr9+LbJ4HA6HVq1aRQEBAXU+Vq5cKXQ5sHY5saa8WPuhoqJC\ne/bsEdnfImpMTEzI399fYHzjxo1kYmJS73ju7u7Ut29fSkhIoDlz5pC2tja9f/+eOb5//36ysLBg\nlbM4SE5OptOnT/ONhYaGUvv27alFixY0ffp0evfunYSykwziek9sbW1p69atzPOkpCTicrm0cuVK\nOnbsGJmYmJCXlxfr/GU0DKqqqo3SYFRTU5Py8vKIiMjQ0JBiY2OJiCg3N5eUlZUlmdpXI5u0SAEV\nFRUkJydH6enpIovZrl07at++/RcfwlBQUED5+fnE4XDo6tWrfFvmHj16RJWVlULnXVhY+FUPNigq\nKjLbemuTk5NDTZo0qXe8p0+fko2NDXE4HFJXV6eIiAi+43Z2dqy3aYsDBwcHWrNmDfM8LS2N5OXl\nadq0abRx40bS0dGhpUuXSi5BCSCu96RFixZ0/fp15rmXlxfZ29szz0+dOkXGxsascpfRcIwYMaLR\nuCLXxsbGho4fP05ERBMmTCAHBwdKTEykSZMmUefOnSWc3dchm7RICYaGhnTz5k1JpyFxaio4dTWJ\n1YyxbRgzMjJiGntrExQUxOqH4+XLl3VO2EpKSvgqL9JCY28gFgfiek+UlJT4Jtu9e/emtWvXMs+F\nbbiXIRmCgoJIR0eH5s6dS3/99Vej0XqKioqiY8eOEVF1U66pqSlxOBxq3rw5xcTESDi7r0PW0yIl\nLFq0CAsWLMD+/fvRrFkzSadTL0S5fY7D4aBt27ZwdXXF8OHDIS8v+o/o3Llz4eHhgZs3b6Jfv37g\ncDhITEzE3r17ERAQIHTcpk2b1jkurf8/X7x4gVatWjHP4+Pj4eDgwDzv3bs37t+/L4nUJIa43hNd\nXV1kZGRAX18fb9++xa1bt7Bp0ybmeElJSaNzB/+WqdEv8vf3Fzgmzcqy9vb2zL8NDQ1x9+5dPH/+\nHFpaWlLrTv0xskmLlBAYGIjc3Fzo6uqiXbt2Ap4QbGTrxcW9e/cwatQopKen87k+13z4hfniPnjw\nAKGhodi7dy+CgoLwv//9D25uboyUuij45ZdfoKOjg40bNyI8PBwAYGpqisOHD2PEiBEiO4+0819r\nIBYF4npPxo4di9mzZ+P333/H6dOnoaOjgz59+jDHU1NT0alTJ5H8DTLEz3/BvqMGTU1N/PPPP9iz\nZw9OnDgh6XS+iGzSIiU0RtdNT09PGBgYICYmps7tc8Kgo6MDX19f+Pr6IjExESEhIbCysoKZmRnc\n3Nzg5uYmEjOyUaNGYdSoUazjNGYcHBwwf/58rF27FidOnICKigrflse0tDQYGRlJMMOGR1zvydKl\nS/Ho0SN4eHhAR0cH+/fv5xOYO3jwIIYPHy6Sv0GG+MjNzYWxsbGk0xAJOTk5CA4ORmhoKF68eMFX\nhZFqJL0+JaPxoq2tTbdu3SKiaq+WzMxMIiI6f/48de/eXWTnKS4uJltbW+JyuVRSUiKSmC9evKBd\nu3bRggULmJjXrl2jBw8eiCR+Y6CxNhCLE9l7IuNzcDgcatu2Lbm4uFBwcHCj20FUVlZGe/fupe++\n+44UFBSIy+VSQEAAvXnzRtKpfTUycTkp49q1a4zgmZmZGXr06CHplD6JlpYWrl27BkNDQxgZGWH3\n7t2wtbVFXl4eunbtirKyMlbxL126hODgYBw5cgSdOnXC1KlT4e7uzrrSkpaWhsGDB6Np06YoKChA\nVlYWDA0NsXjxYhQWFv6/9u4+rub7/x/445x0qVKJhC4laQth+BpdMDSMGGMkl9vM9TX7fczlGDYX\n28wYq4SPi5GLXOWiMrVcJBWSRDQhKaGTdPX+/eHrfJ0V6pzyPuf0uN9u3W7O+31ur/Ng7ZzneV0i\nODhYpfY1zePHj2FsbKzwzR94cb6KsbHxG/f70Vb8N6HynD59GqdOnUJkZCRiYmJQUFAAW1tbdOnS\nBd7e3vD29lZ5j6rqcO7cOWzatAk7d+6Es7Mz/Pz8MHjwYDRu3BgJCQlwdXUVO2LFiV010QuZmZmC\nt7e3IJFIBHNzc8HMzEyQSCRCly5dyt3evzJSU1OF//znP8LgwYPlJ8weOXJEuHz5skrtVsfyubt3\n7wrLli0TmjVrJtSvX1+YOnWqyjn/rWvXrsLMmTMFQRAEY2Nj+b4F0dHRgp2dXZW+FhFpp8LCQuHU\nqVPCwoULBW9vb8HQ0FCQSqWCs7Oz2NHK0NHREaZMmSLvDX+pVq1awpUrV0RKpRwWLWris88+E9q0\naSMkJSXJr125ckVo27atMHjwYKXbjYyMFAwNDYWPPvpI0NPTk39AL1++XPj0009Vyvym5XMnT55U\nqk1dXV3Bzs5OmDdvnhAbGyskJCSU+6MKU1NTITU1VRAExaLl1q1bSu3T8iqJRCK4uroqXHNxcdGY\ncz2IqHLy8/OFY8eOCdOnTxdMTU3V8v/1bt26CSYmJsKQIUOEI0eOCKWlpYIgsGghFZiamgrnzp0r\nc/3s2bNCnTp1lG63Q4cOwsqVKwVBUPyAPnfunNCwYUOl232d7Oxs+f8Qynh1Z93X7bqr6ptC/fr1\n5Rt9vfpvEhYWJjRu3FiltgMDA+W9Ty/t3btXCAoKUqldIlIPz549E06ePCnMnTtX6NSpk6Cvry+4\nuLgIX331lbBt2za1nReXnp4uLFy4ULC3txesrKyESZMmCbVq1VL4oqwJOKdFTZiYmOD06dNo1aqV\nwvWLFy/C09MTT548UapdY2NjXLp0CQ4ODjAxMUFCQgIcHR1x69YtuLi4oKCgQOXsqampuHHjBjw8\nPGBoaAhBEJRe83/79u0KPU+Vs3G+/PJLZGVlYdeuXbCwsEBiYiJ0dHTg6+sLDw8PrFmzRum2iZSR\nnZ2NLVu2YMqUKWJHoTfw9PTE+fPn0aRJE3h4eMDT0xOenp4Ke/toguPHjyMgIAD79u2DjY0NBgwY\ngAEDBqB169ZiR3s7kYsm+l99+vQRPDw8hIyMDPm1O3fuCJ6enoKvr6/S7TZq1EiIjo4WBEGxVyEk\nJERwdHRUKfPDhw+FLl26yHs/XrY9atQoYdq0aSq1XZ0eP34sfPjhh4KZmZmgo6Mj2NjYCLq6uoKH\nh4eQl5cndjyqIUpLS4WjR48KAwcOFPT09ARLS0uxI9Fb1KpVS7CxsREmTpwo7NmzR8jKyhI7kkpy\ncnKEn3/+WWjVqpVaDmuVhz0tauKff/5B3759cfnyZdjY2EAikSA9PR1ubm7Yv38/GjdurFS7s2bN\nQkxMDP788084OzsjLi4OmZmZ8Pf3h7+/P+bPn690Zn9/fzx48ACbNm1C8+bN5b04x44dw9SpU3Hl\nyhWl234XwsPDERcXh9LSUrRu3RofffSRSu3JZDIsW7YMJ0+exIMHD8psQHXz5k2V2iftcOvWLQQE\nBCAoKAgZGRkYOnQo/P394e3tXWa1EqkXmUyG06dPIzIyEhEREYiPj4ezszM8PT3h5eUFT09P1KtX\nT+yYSomLi9OInhYWLWrm+PHjSE5OhiAIcHV1VfmDtKioCCNGjMCOHTsgCAJq1aqFkpISDBkyBEFB\nQSq9STZo0ABhYWFo2bKlwtBTWloa3NzckJeXp1J2TfP555/j1KlTGDZsGKytrcsMkU2ePFmkZCS2\n58+fIyQkBJs2bcLff/+Njz/+GEOGDMHnn3+ueUtOSe7p06eIiopCREQEIiMjkZCQgKZNm+Ly5cti\nR9Na3BFXzXTr1g3dunWrsvZ0dXWxbds2LFq0CBcvXkRpaSnc3d3RtGlTlduWyWTlnpfy8OFD6Ovr\nq9x+dTp37hwiIyPL7REp7zyRijhy5AgOHTqEDz/8sCoikhZp1KgRXF1d4efnh927d8Pc3BzAi0KX\nNFft2rVhYWEBCwsLmJubo1atWrh69arYsbQaixaR2dra4uLFi6hbty4AYO3atfD394epqWmVvk6T\nJk2qfEt2Dw8PBAcHY/HixQBenDlUWlqKH374Ad7e3lX6WlVp6dKlmDt3Lpo1awYrKyuFHhFVDg0z\nNzdX28MRSVwlJSWQSCSQSCQcAtJgpaWliI2NlQ8PRUdHQyaToVGjRvD29savv/6q1u992oDDQyKT\nSqW4f/8+6tevDwAwNTVFfHw8HB0dq6T9kpISBAUFvXaeRXh4uNJtJyUlwcvLC23atEF4eDj69OmD\nK1euICcnB9HR0SoVSQsWLMDIkSNVWiX0OlZWVli+fDlGjBhRpe1u3boV+/fvx+bNm3liLykoKCjA\nnj178Mcff+DMmTP4+OOP4efnh0GDBiE+Pp7DQxrC1NQUMpkM1tbW8PLygpeXF7y9vdX6jK4DBw7g\n448/1prDT1m0iOzfRcurc0OqwoQJExAUFIRevXqVO89i9erVKrV///59/Pbbb7hw4YJ8Quv48eNh\nbW2tUrtt2rRBQkICPD09MXr0aPTv3x8GBgYqtfmStbU1/vrrryoZInN3d1f4N01NTYUgCLC3ty/z\nJqGOJ3XTu3fjxg0EBgZi8+bNyMjIwOeff44RI0agS5cu7IVRcxs2bIC3tzecnZ3FjlJhOjo6uH//\nPurVqwcdHR3cu3dP/nmjiVi0iKy6ixZLS0sEBwejZ8+eVdLeS8XFxViyZAlGjRoFGxubKm37pcTE\nRAQGBuK///0vCgsLMXjwYIwaNQoffPCBSu2uWLECd+/erZL9WBYuXFjh56qyUou0T2lpKcLCwvDH\nH38gNDQUJiYmePjwodixSMs0aNAAGzduxCeffAKpVIrMzEyNXeEEsGgRnVQqxXfffQelrRTCAAAg\nAElEQVRjY2MAwOzZszFz5kxYWloqPG/SpElKtd+wYUNERkZWyzcDY2NjXL58Gfb29lXe9quKi4sR\nGhqKwMBAHD16FM2aNcOYMWMwYsQI1KlTp9LtlZaWolevXkhJSYGrq2uZHpGQkJCqik5UIVlZWdiy\nZQumTZsmdhTSMgsWLMCiRYsqNF+vpKTkHSRSDYsWkdnb27/1l0kikSi9x8fKlStx8+ZNrF27VqVJ\npuXx9fWFr69vlc8N+bfCwkLs3bsXAQEBCA8PR8eOHZGZmYm7d+9i48aNGDRoUKXaGz9+PP744w94\ne3uXmYgLAIGBgUrlPH/+PEpLS9G+fXuF62fPnoWOjg7atm2rVLtERKpITk5Gamoq+vTpg8DAQJiZ\nmZX7vL59+77jZJXHokUL9e/fX+FxeHg4LCws8N5771Vpr8KGDRuwYMECDB06FG3atEHt2rUV7vfp\n00fptgHgwoULCAwMxPbt26Gvrw9/f3+MGTMGTk5OAF4UZCtWrEBmZmal2jUxMcGOHTvQq1cvlfL9\nW7t27TBr1iwMGDBA4XpISAiWL1+Os2fPVunrERFVxsKFCzFz5kyNXijAokULjRw5ssLPVbZXAXgx\ntPU6EolEpa7GFi1a4OrVq+jevTu++OILfPLJJ2UmKWZlZcHKyqrMiqi3sbOzQ1hYGFxcXJTOVx5j\nY2MkJiaWmY+UlpaGFi1a4OnTp1X6ekREysjKysK1a9cgkUjg7OysUXNcuE+LFgoMDER6ejoaN278\nxsJCVZUtFipj4MCBGDVqFBo1avTa59SrV0+pDAsWLMD8+fMRGBhYpd849PX1kZmZWaZouXfvHmrV\n4v9qRCSu/Px8TJgwAVu2bJF/qdTR0YG/vz9++eUXjeiBYU+LltKGpW3Ai/ksaWlpaNKkSZV98Lu7\nu+PGjRtVvjR58ODBuH//Pvbv3y+fIJybmwtfX1/Ur18fu3btUjk7EZGyvvrqK5w4cQJr166V79wd\nFRWFSZMmoVu3bvjtt99ETvh2LFq01L+XUlelZ8+e4eTJk+jduzcA4JtvvsHz58/l93V0dLB48WKV\n9lV59uwZJkyYgM2bNwMAUlJS4OjoiEmTJqFhw4aYM2eO0m2/bZmyskuTMzIy4OHhgezsbLi7uwMA\n4uPjYWVlhePHj1fb0nDSLH/99ReMjIwUJmbHxsYiPz8fHh4eIiYjbWdpaYndu3fDy8tL4XpERAQ+\n++wzZGVliROsEli0iGjatGlYvHgxateujb/++gsdO3asst6E6ixaNmzYgIMHDyI0NBTAi4mt7733\nHgwNDQG8mKk+a9YsTJ06VenXmDx5MqKjo7FmzRr4+PjI54ocOHAA8+fPx8WLF6vk71LVZDIZtm3b\nhoSEBBgaGqJFixb4/PPPtWY3SlKdVCqFi4sLkpKS5NeaN2+OlJQUjVhySprLyMgIFy5cQPPmzRWu\nX7lyBe3atYNMJhMpWcWxaBGRrq4u7ty5Aysrqyofzvn3/i+vo8z+Lx4eHpg6dSr69esHoOyGeFu3\nbsWvv/6KmJiYygf/X3Z2dti5cyc6dOig0H5qaipat26NJ0+eKN32SxcuXMDVq1chkUjg6uoq7x0h\nqk63b9+Grq4uGjZsKL929+5dFBUVVcuxFUQvde3aFXXr1kVwcLC8J/zZs2cYPnw4cnJycOLECZET\nvh1nB4rI3t4eP//8M7p37w5BEBATEyM//fXflOk2Xr9+/Ru3BZdIJEoVLSkpKQqb1RkYGChM+G3X\nrh3Gjx9f6XZflZWVVW4BJ5PJVN5v5sGDBxg8eDAiIyNhZmYGQRDw+PFjeHt7Y8eOHZWaSf/quR4H\nDhx443NVXQJO2qG8wuTVAoaouvz000/w8fFB48aN0bJlS0gkEsTHx8PAwABhYWFix6sQ9rSIaN++\nfRg7diwePHgAiUSC1/2nUGb5cHUODxkaGiI+Ph7NmjUr935ycjJatWqFgoICpV/D09MTAwYMwMSJ\nE2FiYoLExEQ4ODhgwoQJSE1NxdGjR5Vue9CgQbhx4wa2bNki7yZNSkrC8OHD4eTkhO3bt1e4rVf/\nnatzCThpl8LCwnIPMLW1tRUpEdUUz549w9atW5GcnAxBEODq6oqhQ4fKh/fVHXtaRPRyR9m8vDyY\nmpri2rVrVVZkVPXut69q3LgxLl++/NqiJTExEY0bN1bpNb7//nv4+PggKSkJxcXF+Omnn3DlyhXE\nxMTg1KlTKrV99OhRnDhxQmFc19XVFb/++iu6d+9eqbZe/dCpziXgpB2uX7+OUaNG4e+//1a4LggC\nC1t6JwwNDfHFF1+IHUNp1beJB1WYsbExIiIi4ODggDp16pT7U1nV2YHWs2dPzJs3r9yelGfPnmHh\nwoUq7zbbsWNHREdHIz8/H02aNMGxY8dgZWWFmJgYtGnTRqW2S0tLy50Yq6urq3ThUVRUBG9vb6Sk\npKiUjbTbiBEjIJVKcfDgQVy4cAFxcXGIi4vDxYsXeQo4UQVweEiNlJSUYN++ffLJoc2bN0ffvn2V\nOq6+OrdrzszMRKtWraCnp4cJEybA2dkZEokEycnJWLt2LYqLi3Hx4kVYWVlV+WtXhb59+yI3Nxfb\nt2+XzyXIyMjA0KFDYW5ujr179yrVbr169fD333+jadOmVRmXtEjt2rVx4cKFKt+NmaimYNGiJlJT\nU9GrVy/cuXMHzZo1gyAISElJgY2NDQ4dOoQmTZqIHVFBWloavv76axw/flzeqyORSNCtWzesW7eu\nzK6wyigtLUVqamq5Y/+q7Gfxzz//oG/fvrh8+TJsbGwgkUiQnp4ONzc37N+/X+mhrenTp0NXVxfL\nli1TOhtptw8++ACrV69Gp06dxI5CpJFYtKiJnj17QhAEbNu2DRYWFgCA7Oxs+Pn5QSqV4tChQyIn\nLF9OTg5SU1MBAE5OTvLsqjpz5gyGDBmC27dvlxnqqqqx/+PHjytMRvvoo49Uam/ixIkIDg6Gk5MT\n2rZtW+YAyVWrVqnUPmm+8PBwzJ07F0uXLoWbm1uZYUpTU1ORkhFpBhYtaqJ27do4c+YM3NzcFK4n\nJCTgww8/RF5enkjJxNGqVSs4Oztj4cKFsLa2LjOxWJl5PtXN29v7jfcjIiLeURJSVy9XmP3795kT\nceldcHR0xPnz51G3bl2F67m5uWjdujVu3rwpUrKK4+ohNaGvr1/uKcB5eXnQ09MTIZG4rl+/jt27\nd8PJyanK2jx79ixycnLw8ccfy68FBwdj/vz5kMlk8PX1xS+//AJ9fX2l2mdRQm/D3xES061bt8ot\njJ8/f46MjAwRElUeixY10bt3b3z55Zf4448/0K5dOwAvPmTHjh1bIzcla9++PVJTU6u0aFmwYAG8\nvLzkRculS5cwevRojBgxAs2bN8cPP/yAhg0bYsGCBUq1P2rUKPz0008wMTFRuC6TyTBx4kQEBASo\n+lcgDefp6Sl2BKqBXt34MiwsTKGnuqSkBCdPnoS9vb0IySqPw0NqIjc3F8OHD0doaKh8nLu4uBh9\n+vRBUFCQSsMhixYtgqWlJcaNGye/tm7dOjx8+BDz5s1TOXtVSUxMlP/5xo0bmDt3LmbOnFnu2H+L\nFi0q3b61tTVCQ0PlB9X95z//walTpxAVFQUA+PPPPzF//nyFM2Eq43VHMTx8+BANGjRAcXGxUu2S\nZktMTMT7778PqVSq8DteHmV+r4ne5tVhyX9/5Ovq6sLe3h4rV66UH4Krzli0qJnU1FRcvXpVPjm0\nKnoaHBwc4OTkhOPHj8uvde3aFWlpaWo1himVSt+6M7AqY/8GBga4fv26/LTlTp06wcfHB3PnzgXw\nouvUzc2t3GG6N3ny5AkEQYC5uTmuX7+ucAxASUkJQkNDMWfOHNy9e7fSmUnz/XvX5Nf9jnNOC1U3\nBwcHnD9/HpaWlmJHURqHh9SMk5NTlQ6JAC+WJ//byZMnq/Q1qkJ5OauSlZUV0tLSYGNjg8LCQsTF\nxWHhwoXy+0+fPlXqNGYzMzNIJBJIJBKFM5lekkgkCq9DNUtaWpq8kK3u33GiNynv9y83NxdmZmYi\npFEOixZSG3Z2dq+dF1IVfHx8MGfOHCxfvhz79u2DkZEROnfuLL+fmJio1H44EREREAQBXbp0wZ49\nexSWfevp6cHOzo4H4tVgrx6Q+LpTnDMzM7Fhwwa1Gq4l7bN8+XLY29tj0KBBAICBAwdiz549sLa2\nxuHDh9GyZUuRE74dh4e03NGjR2FsbCzfzOrXX3/Fxo0b5WftvO5UabG8bl5IVcjKykL//v0RHR0N\nY2NjbN68Gf369ZPf79q1Kzp06IAlS5Yo1f7t27dha2tbrec+kXZKSEhA69atOTxE1crR0RFbt25F\nx44dcfz4cXz22WfYuXMndu3ahfT0dBw7dkzsiG/FokXLubm5Yfny5ejZsycuXbqEDz74ANOmTUN4\neDiaN2+OwMBAsSMqqM7TqV96/PgxjI2NyxyPkJOTA2NjY5WWmJ8+fRobNmzAzZs38eeff6JRo0bY\nsmULHBwcuAsqvRaLFnoXDA0N5TutT548GQUFBdiwYQNSUlLQvn17PHr0SOyIb8UDE9VEenp6uZPz\nBEFAenq60u2mpaXB1dUVALBnzx707t0bS5cuxbp163DkyBGl261O1d1TUadOnXLPc7KwsFCpYNmz\nZw969OgBQ0NDxMXF4fnz5wBezJVZunSp0u0SEVUFc3Nz/PPPPwBe9MK/3AVcEASNKZhZtKgJBwcH\nZGVllbmek5MDBwcHpdvV09NDfn4+AODEiRPo3r07gBcf0E+ePFG63erk7OwMCwuLN/6oo++++w7r\n16/Hxo0bFSb0duzYkSf4EpHo+vfvjyFDhqBbt27Izs6W71kVHx9f5QtAqgsn4qqJl0t5/y0vLw8G\nBgZKt9upUydMmzYNH374Ic6dO4edO3cCAFJSUpQ+GLC6LVy4UC236X+ba9eulXuQo6mpKXJzc0VI\nROpi2rRpb7xf3hcWoqq2evVq2Nvb459//sGKFStgbGwMALh3757CPl7qjEWLyF6+mUkkEnz77bcw\nMjKS3yspKcHZs2fRqlUrpdtfu3Ytxo0bh927d+O3335Do0aNAABHjhyBj4+PauGryeDBg6t1Tkt1\nsba2RmpqapmdJaOioqrk1GvSXBcvXnzrc1Q5uZyoInR1dTFjxowy16dMmSJCGuWwaBHZyzczQRBw\n6dIlhTkVenp6aNmyZbm/ZBVla2uLgwcPlrm+evVqpdusTpq88uarr77C5MmTERAQAIlEgrt37yIm\nJgYzZszgUtYajmcOkbrYsmWLfLFATEwM7OzssGbNGjg4OKBv375ix3srFi0ie/lmNnLkSPz0009V\ncjR9ZeaqVMXrVSVNXsw2a9YsPH78GN7e3igoKICHhwf09fUxY8YMTJgwQex4RFTD/fbbb5g3bx6m\nTJmCJUuWyCffmpmZYc2aNRpRtHDJsxZ6uVX4m6iyHT69WX5+PpKSklBaWgpXV1f5uDERkZhcXV2x\ndOlS+Pr6wsTEBAkJCXB0dMTly5fh5eWFhw8fih3xrdjToiZkMhmWLVuGkydP4sGDBygtLVW4X5kz\ngtgVLS4jIyP5oYxEROoiLS0N7u7uZa7r6+tDJpOJkKjyWLSoiTFjxuDUqVMYNmwYrK2tVZrb4enp\nWYXJ6E369++PoKAgmJqaon///m98bkhIyDtKRURUloODA+Lj48scJ3HkyBH5fl7qjkWLmjhy5AgO\nHTqEDz/8sMrb5i6t1adOnTryAlMTl2kTUc0xc+ZMjB8/HgUFBRAEAefOncP27dvx/fffY9OmTWLH\nqxAWLWrC3Ny8WjZN27NnD4YNG4ahQ4eWu0vr4cOHq/w1a5JXj0FQtyMRSH3l5+cjPT0dhYWFCtdb\ntGghUiKqCUaOHIni4mLMmjUL+fn5GDJkCBo1aoSffvoJgwcPFjtehXAirprYunUr9u/fj82bNyvs\n1aIqd3d3TJ06Ff7+/goTr+Lj4+Hj44P79+9X2WsR8PDhQ9y6dQsSiQT29vaoW7eu2JFIjWRlZWHk\nyJGvPUKDE+PpXXn48CFKS0s1bk8s9rSoiZUrV+LGjRuwsrKCvb29wjbwAJTeBp67tL4bV65cwddf\nf43o6GiF656enli3bh1cXFxESkbqZMqUKXj06BHOnDkDb29v7N27F5mZmfjuu++wcuVKseNRDWJp\naYnCwkLk5eVp1ApHFi1qwtfXt1ra5S6t1e/+/fvw9PREvXr1sGrVKri4uEAQBCQlJWHjxo3w8PDA\n5cuXNe4bDVW98PBw7N+/Hx988AGkUins7OzQrVs3mJqa4vvvv0evXr3EjkhaKjAwEHFxcejQoQOG\nDh2Kb775BqtWrUJxcTG6dOmCHTt2aEbPsEBabfny5YKrq6tw5swZwcTERDh9+rSwdetWoV69esIv\nv/widjytMGvWLKF169bCs2fPytzLz88XWrduLcyZM0eEZKRuTExMhLS0NEEQBMHOzk6IiooSBEEQ\nbt68KRgaGoqYjLTZd999JxgaGgpdu3YVLCwshLFjxwoNGjQQli1bJqxYsUJo3LixMHbsWLFjVgiL\nlhrg//2//ycYGhoKEolEkEgkgoGBgTB37lyxY2kNd3d3YefOna+9v337dsHd3f0dJiJ11bZtW+Ho\n0aOCIAhC3759hWHDhgl37twRZs2aJTg6OoqcjrSVk5OT8N///lcQBEE4f/68IJVKhT///FN+//Dh\nw4Ktra1Y8SqFE3FFZGFhgZSUFFhaWsLc3PyNe7Pk5OSo9FrcpbX6mJmZITY29rVHu6empqJt27ac\nQ0TYtm0bioqKMGLECFy8eBE9evRAdnY29PT0EBQUhEGDBokdkbSQvr4+UlNTYWNjI3+cmJiIZs2a\nAQAyMjLg4OBQZjWbOuKcFhGtXr0aJiYmAIA1a9ZU62txl9bq8/Tp0zee4WRiYoK8vLx3mIjU1dCh\nQ+V/dnd3x61bt5CcnAxbW1tYWlqKmIy0WVFREfT19eWP9fT0FBZ71KpVS2NWrrFoEdHw4cPL/XNV\n6tevX7k9OBKJBAYGBnBycsKQIUPkFTcp5+nTpzAwMCj33pMnTzT6IEiqOpGRkfDy8pI/NjIyQuvW\nrcULRDVGUlKSfIsLQRCQnJws/zKlCWcOvcThITX07NkzFBUVKVxT9jTmESNGYN++fTAzM0ObNm0g\nCAIuXryI3NxcdO/eHQkJCbh16xZOnjxZLbvx1gRvO6BS4OGU9L8MDAzQqFEjjBw5EsOHD5d31xNV\np5fvUeV93L+8rinvUSxa1IRMJsPs2bOxa9cuZGdnl7mv7C/TnDlz8OTJE6xduxZSqRQAUFpaismT\nJ8PExARLlizB2LFjceXKFURFRan0d6ipTp06VaHn8UwoysnJwdatWxEUFITExER07doVo0ePhq+v\nL/T09MSOR1rq9u3bFXrev88kUkcsWtTE+PHjERERgUWLFsHf3x+//vorMjIysGHDBixbtkxhLLwy\n6tWrh+joaDg7OytcT0lJQceOHfHw4UNcunQJnTt35kRRoncoPj4eAQEB2L59O0pLSzF06FCMHj0a\nLVu2FDsakdqSih2AXggNDcW6deswYMAA1KpVC507d8bcuXOxdOlSbNu2Tel2i4uLkZycXOZ6cnKy\nvPfGwMBApVOliajyWrVqhTlz5mD8+PGQyWQICAhAmzZt0LlzZ1y5ckXseERqiUWLmsjJyYGDgwOA\nF/NXXi5x7tSpE/766y+l2x02bBhGjx6N1atXIyoqCtHR0Vi9ejVGjx4Nf39/AC+GN9577z3V/xJE\n9FZFRUXYvXs3evbsCTs7O4SFhWHt2rXIzMxEWloabGxsMHDgQLFjEqklrh5SE46Ojrh16xbs7Ozg\n6uqKXbt2oV27dggNDYWZmZnS7a5evRpWVlZYsWIFMjMzAQBWVlaYOnUqZs+eDQDo3r07fHx8quTv\nQUSvN3HiRGzfvh0A4OfnhxUrVuD999+X369duzaWLVtW5tgNInqBc1rUxOrVq6Gjo4NJkyYhIiIC\nvXr1QklJCYqLi7Fq1SpMnjxZ5dd48uQJAOVXIhGRarp27YoxY8bg008/fe3E2+LiYkRHR3PiNlE5\nWLSoqdu3b+PChQto0qQJJ+ZpmNTUVNy4cQMeHh4wNDSULyckIhJbcXExIiMjcePGDQwZMgQmJia4\ne/cuTE1NNWKndBYtWi4zMxMzZszAyZMn8eDBgzLr9DVhXb6myM7OxqBBgxAeHg6JRILr16/D0dER\no0ePhpmZGVauXCl2RFITSUlJSE9PL7Ntep8+fURKRDXB7du34ePjg/T0dDx//hwpKSlwdHTElClT\nUFBQgPXr14sd8a04p0VkZ8+eRU5ODj7++GP5teDgYMyfPx8ymQy+vr745ZdfFLZgrowRI0YgPT0d\n3377LaytrfmNvxpNnToVtWrVQnp6Opo3by6/PmjQIEydOpVFC+HmzZvo168fLl26pLDZ18v/L/kl\ngqrT5MmT0bZtWyQkJKBu3bry6/369cOYMWNETFZxLFpEtmDBAnh5ecmLlkuXLmH06NEYMWIEmjdv\njh9++AENGzbEggULlGo/KioKp0+fRqtWraowNZXn2LFjCAsLQ+PGjRWuN23atMKbO5F2mzx5Mhwc\nHHDixAk4Ojri3LlzyM7OxvTp0/Hjjz+KHY+03MsVpP+eT2VnZ4eMjAyRUlUOlzyLLD4+Hl27dpU/\n3rFjB9q3b4+NGzdi2rRp+Pnnn7Fr1y6l27exseG5N++ITCaDkZFRmesPHz5UuqeMtEtMTAwWLVqE\nevXqQSqVQiqVolOnTvj+++8xadIkseORlistLS23N+/OnTvyw3vVHYsWkT169AhWVlbyx6dOnVJY\nfvzBBx/gn3/+Ubr9NWvWYM6cObh165YqMakCPDw8EBwcLH8skUhQWlqKH374Ad7e3iImI3VRUlIi\nn+xoaWmJu3fvAnjxTffatWtiRqMaoFu3blizZo38sUQiQV5eHubPn4+ePXuKmKziODwkMisrK/mG\nUoWFhYiLi8PChQvl958+fapwhHhlDRo0CPn5+WjSpAmMjIzKtPVyEztS3Q8//AAvLy/ExsaisLAQ\ns2bNwpUrV5CTk4Po6Gix45EaeP/995GYmAhHR0e0b98eK1asgJ6eHn7//Xc4OjqKHY+03OrVq+Ht\n7Q1XV1cUFBRgyJAhuH79OiwtLeX7B6k7Fi0i8/HxwZw5c7B8+XLs27cPRkZG6Ny5s/x+YmIimjRp\nonT7r1bVVL1cXV2RmJiI3377DTo6OpDJZOjfvz/Gjx8Pa2trseORGpg7dy5kMhkA4LvvvkPv3r3R\nuXNn1K1bFzt37hQ5HWm7hg0bIj4+Htu3b0dcXBxKS0sxevRoDB06FIaGhmLHqxAueRZZVlYW+vfv\nj+joaBgbG2Pz5s3o16+f/H7Xrl3RoUMHLFmypFpeu169elXeLhFVXE5ODszNzbmyj6gCWLSoiceP\nH8PY2Bg6OjoK13NycmBsbFxlx9YLgoAjR45g06ZNOHToEJ4/f14l7dILubm5OHfuHB48eIDS0lKF\ney/PeiIiEktKSgoiIyPLfY+aN2+eSKkqjkVLDXHz5k0EBARg8+bNyMvLQ69evfDpp58q9OqQakJD\nQzF06FDIZDKYmJgofHOWSCScP1SDjRo1qkLPCwgIqOYkVJNt3LgRX3/9NSwtLdGgQYMy71FxcXEi\npqsYFi1arKCgALt378amTZtw5swZdOvWDUeOHEF8fLzCIW1UNZydndGzZ08sXbq03KXPVHNJpVLY\n2dnB3d39jVsQ7N279x2moprGzs4O48aNkx+Wq4k4EVdLjRs3Djt27ECzZs3g5+eHPXv2oG7dutDV\n1YVUypXu1SEjIwOTJk1iwUJljB07Fjt27MDNmzcxatQo+Pn5wcLCQuxYVMM8evQIAwcOFDuGSvjp\npaV+//13fP311zh27BjGjx+vsGUzVY8ePXogNjZW7BikhtatW4d79+5h9uzZCA0NhY2NDT777DOE\nhYVx80d6ZwYOHIhjx46JHUMl7GnRUsHBwQgMDIS1tTV69eqFYcOGKWxaR1WvV69emDlzJpKSkuDm\n5lZmTxwehlez6evr4/PPP8fnn3+O27dvIygoCOPGjUNRURGSkpI04oRd0jw///yz/M9OTk749ttv\ncebMmXLfozRhV2bOadFyt27dQmBgIIKCgpCfn4+cnBzs3LkTAwYMEDua1nnTsJtEIuFheCSXnp6O\noKAgBAUFobCwEMnJySxaqFo4ODhU6HkSiQQ3b96s5jSqY9FSQwiCgLCwMAQEBODAgQOwtLRE//79\nFapwIqo+z58/R0hICAICAhAVFYXevXtj5MiR8PHx4Twzogpi0VID5eTkyIePEhISxI6jlQoKCmBg\nYCB2DFITLyfG29raYuTIkfDz8+M8M3pnHB0dcf78ea34nWPRQlRFSkpKsHTpUqxfvx6ZmZlISUmB\no6Mjvv32W9jb22P06NFiRySRSKVS2Nrawt3d/Y0734aEhLzDVFRTSKVS3L9/H/Xr1xc7isrYJ0lU\nRZYsWYKgoCD5IXgvubm5YdOmTSImI7H5+/vD29sbZmZmqFOnzmt/iOjN2NNCVEWcnJywYcMGdO3a\nFSYmJkhISICjoyOSk5PxP//zP3j06JHYEYmoBpJKpQgPD3/r3kAtWrR4R4mUxyXPRFUkIyMDTk5O\nZa6XlpaiqKhIhERERC907dq13D2BJBIJBEHQmBWOLFqIqsh7772H06dPw87OTuH6n3/+CXd3d5FS\nEREBZ8+eRb169cSOoTIWLVouMTGx3OsSiQQGBgawtbWFvr7+O06lnebPn49hw4YhIyMDpaWlCAkJ\nwbVr1xAcHIyDBw+KHY+IajBbW1utmIjLOS1aTiqVvnG1gq6uLgYNGoQNGzZwiW4VCAsLw9KlS3Hh\nwgWUlpaidevWmDdvHrp37y52NCKqobRp9RCLFi23f/9+zJ49GzNnzkS7du0gCEmjwmQAABWWSURB\nVALOnz+PlStXYv78+SguLsacOXMwaNAg/Pjjj2LHJSKiKubt7Y29e/fCzMxM7CgqY9Gi5dq1a4fF\nixejR48eCtfDwsLw7bff4ty5c9i3bx+mT5+OGzduiJSSiIjo7TinRctdunSpzMRQALCzs8OlS5cA\nAK1atcK9e/fedTStYG5u/sbht1fl5ORUcxoiIu3GokXLubi4YNmyZfj999/lG54VFRVh2bJlcHFx\nAfBiqa6VlZWYMTXWmjVrxI5ARFRjcHhIy/3999/o06cPpFIpWrRoAYlEgsTERJSUlODgwYPo0KED\ntmzZgvv372PmzJlix9VYxcXF2LZtG3r06IEGDRqIHYeISCuxaKkB8vLysHXrVqSkpEAQBLi4uGDI\nkCEwMTERO5pWMTIywtWrV8sdjiMiItVxeKgGMDY2xtixY8WOofXat2+PixcvsmghIrX1119/wcjI\nCG3btpVfi42NRX5+Pjw8PERMVjHsaakBUlJSEBkZiQcPHqC0tFTh3rx580RKpX3+/PNPzJkzB1On\nTkWbNm1Qu3ZthfuacK4HEWk3qVQKFxcXJCUlya81b94cKSkpGrGNP4sWLbdx40Z8/fXXsLS0RIMG\nDRRWukgkEsTFxYmYTrtIpWUPTde0cz2ISLvdvn0burq6aNiwofza3bt3UVRUpBG9xCxatJydnR3G\njRuH2bNnix1F692+ffuN9zXhDYGISJ2xaNFypqamiI+Ph6Ojo9hRiIhIRI6Ojjh//jzq1q2rcD03\nNxetW7fGzZs3RUpWcZyIq+UGDhyIY8eOcSLuO5SUlIT09HQUFhYqXO/Tp49IiYiIgFu3bpU7TP38\n+XNkZGSIkKjyWLRoOScnJ3z77bc4c+YM3NzcoKurq3B/0qRJIiXTPjdv3kS/fv1w6dIl+VwWAPJ5\nRJzTQkRiOHDggPzPYWFhqFOnjvxxSUkJTp48CXt7exGSVR6Hh7Scg4PDa+9JJBKN6A7UFJ988gl0\ndHSwceNGODo64ty5c8jOzsb06dPx448/onPnzmJHJKIa6OUigVe/TL2kq6sLe3t7rFy5Er179xYj\nXqWwaCGqIpaWlggPD0eLFi1Qp04dnDt3Ds2aNUN4eDimT5+Oixcvih2RiGowBwcHnD9/HpaWlmJH\nUVrZNZpEpJSSkhIYGxsDeFHA3L17F8CLVUPXrl0TMxoREdLS0jS6YAE4p0UrTZs2DYsXL0bt2rUx\nbdq0Nz531apV7yiV9nv//feRmJgIR0dHtG/fHitWrICenh5+//13rt4iIlH8/PPP+PLLL2FgYICf\nf/75jc/VhDmOHB7SQt7e3ti7dy/MzMzg7e392udJJBKEh4e/w2TaLSwsDDKZDP3798fNmzfRu3dv\nJCcno27duti5cye6dOkidkQiqmEcHBwQGxuLunXrasUcRxYtRNUoJycH5ubmCjsRExGRcli0EBER\nkUbgnBYtJ5PJsGzZMpw8ebLcAxM1oTtQ3Y0aNapCzwsICKjmJERErycIAnbv3o2IiIhyPw9CQkJE\nSlZxLFq03JgxY3Dq1CkMGzYM1tbWHKaoBkFBQbCzs4O7u3uZPRCIiNTF5MmT8fvvv8Pb2xtWVlYa\n+XnA4SEtZ2ZmhkOHDuHDDz8UO4rWGjduHHbs2AFbW1uMGjUKfn5+sLCwEDsWEZECCwsLbN26FT17\n9hQ7itK4T4uWMzc35wdoNVu3bh3u3buH2bNnIzQ0FDY2Nvjss88QFhbGnhciUht16tTR+O0X2NOi\n5bZu3Yr9+/dj8+bNMDIyEjtOjXD79m0EBQUhODgYRUVFSEpKkm86R0Qkls2bN+Po0aMICAiAoaGh\n2HGUwjktWm7lypW4ceMGrKysYG9vX+bAxLi4OJGSaS+JRCI/4+PfE92IiMQycOBAbN++HfXr19fY\nzwMWLVrO19dX7Ag1wvPnzxESEoKAgABERUWhd+/eWLt2LXx8fOSHlRERiWnEiBG4cOEC/Pz8OBGX\nqKZ6dSLuyJEj4efnh7p164odi4hIQe3atREWFoZOnTqJHUVpLFqIVCSVSmFrawt3d/c3fnPRhD0Q\niEh7ubi4YNeuXWjRooXYUZTG4SEtZGFhgZSUFFhaWr51C/mcnJx3mEw7+fv7a2Q3KxHVLCtXrsSs\nWbOwfv162Nvbix1HKexp0UKbN2/G4MGDoa+vj82bN7/xucOHD39HqYiISEzm5ubIz89HcXExjIyM\nykzE1YQvsSxaiIiIagBt+BLLoqUGefbsGYqKihSumZqaipSGiIiocjinRcvJZDLMnj0bu3btQnZ2\ndpn7JSUlIqQiIiIxlJSUYN++fbh69SokEglcXV3Rp08f6OjoiB2tQli0aLlZs2YhIiIC69atg7+/\nP3799VdkZGRgw4YNWLZsmdjxiIjoHUlNTUXPnj2RkZGBZs2aQRAEpKSkwMbGBocOHUKTJk3EjvhW\nHB7Scra2tggODoaXlxdMTU0RFxcHJycnbNmyBdu3b8fhw4fFjkhERO9Az549IQgCtm3bJj+TLjs7\nG35+fpBKpTh06JDICd+ORYuWMzY2xpUrV2BnZ4fGjRsjJCQE7dq1Q1paGtzc3JCXlyd2RCIiegdq\n166NM2fOwM3NTeF6QkICPvzwQ434POD+4lrO0dERt27dAgC4urpi165dAIDQ0FCYmZmJmIyIiN4l\nfX19PH36tMz1vLw86OnpiZCo8li0aLmRI0ciISEBAPDNN99g3bp10NfXx9SpUzFz5kyR0xER0bvS\nu3dvfPnllzh79iwEQYAgCDhz5gzGjh2LPn36iB2vQjg8VMOkp6cjNjYWTZo0QcuWLcWOQ0RE70hu\nbi6GDx+O0NBQ+cZyxcXF6NOnD4KCglCnTh2RE74dixYtFxwcjEGDBkFfX1/hemFhIXbs2AF/f3+R\nkhERkRhSU1Nx9epVCIIAV1dXODk5iR2pwli0aDkdHR3cu3cP9evXV7ienZ2N+vXrc58WIqIaoKio\nCM2aNcPBgwfh6uoqdhylcU6LlhMEodzD/O7cuaMRXYFERKQ6XV1dPH/+XOMPd+XmclrK3d0dEokE\nEokEXbt2Ra1a//efuqSkBGlpafDx8RExIRERvUsTJ07E8uXLsWnTJoXPBE2imanprXx9fQEA8fHx\n6NGjB4yNjeX39PT0YG9vj08//VSseERE9I6dPXsWJ0+exLFjx+Dm5obatWsr3A8JCREpWcWxaNFS\n8+fPR0lJCezs7NCjRw9YW1uLHYmIiERkZmam8V9WORFXyxkYGODq1atwcHAQOwoREZFKOBFXy7m5\nueHmzZtixyAiIlIZixYtt2TJEsyYMQMHDx7EvXv38OTJE4UfIiLSbjdu3MCoUaPkj21tbWFhYSH/\nqVevHq5duyZiworj8JCWk0r/ry59danby6XQ3KeFiEi7TZkyBUZGRli6dCkAwMTEBPPmzZPv37Vz\n507Y2tpi/fr1YsasEE7E1XIRERFiRyAiIhGdOHECv/zyi8K1Tz/9FI6OjgAAe3t7jBkzRoxolcai\nRct5enqKHYGIiER0+/ZthcUYY8aMUdhc1N7eHnfu3BEjWqVxTksNcPr0afj5+aFjx47IyMgAAGzZ\nsgVRUVEiJyMiouomlUrx4MED+ePVq1ejbt268seZmZnyAxTVHYsWLbdnzx706NEDhoaGiIuLw/Pn\nzwEAT58+lY9vEhGR9nrvvfdw4sSJ194PCwvD+++//w4TKY9Fi5b77rvvsH79emzcuFGhku7YsSPi\n4uJETEZERO/CyJEjsWTJEhw6dKjMvdDQUCxbtgwjR44UIVnlcU6Llrt27Ro8PDzKXDc1NUVubq4I\niYiI6F364osvEB4ejk8++QQuLi5o1qwZJBIJkpOTce3aNXz66af44osvxI5ZIexp0XLW1tZITU0t\ncz0qKko+c5yIiLTb9u3b8d///hfOzs64du0akpOT0bRpU2zbtg27du0SO16FsadFy3311VeYPHky\nAgICIJFIcPfuXcTExGDGjBmYN2+e2PGIiOgdGTx4MAYPHix2DJVwc7ka4D//+Q9Wr16NgoICAIC+\nvj5mzJiBxYsXi5yMiIio4li01BD5+flISkpCaWkpXF1dYWxsLHYkIiKiSuGcFi03atQoPH36FEZG\nRmjbti3atWsHY2NjyGQyhbMoiIiI1B17WrScjo4O7t27Jz9j4qWHDx+iQYMGKC4uFikZERFR5bCn\nRUs9efIEjx8/hiAIePr0qcLJzo8ePcLhw4fLFDJERKT9Hj16VObamTNnREhSeVw9pKXMzMwgkUgg\nkUjg7Oxc5r5EIsHChQtFSEZERGKqW7cumjdvjlGjRmH8+PE4cOAARo4cCZlMJna0t2LRoqUiIiIg\nCAK6dOmCPXv2wMLCQn5PT08PdnZ2aNiwoYgJiYhIDOfPn8elS5ewadMmrFq1CllZWViwYIHYsSqE\nc1q03O3bt2FjYwOplCOBREQ10fXr1wEATZs2Vbi+ZMkSLF68GHp6ejh//jyaNWsmRrxKYdFSA+Tm\n5uLcuXN48OABSktLFe75+/uLlIqIiN6FLl26YNy4cRgwYID82oYNGzBz5kyEhITg6NGj+Oeff7Bz\n504RU1YMixYtFxoaiqFDh0Imk8HExAQSiUR+TyKRICcnR8R0RERU3czMzBAXFyc/umX37t0YO3Ys\nDhw4gI4dO+LixYv46KOPkJ2dLXLSt+OYgZabPn26fK+W3NxcPHr0SP7DgoWISPtJpVI8ePAAABAW\nFoZp06bhxIkT6NixI4AX8xxLSkrEjFhhnIir5TIyMjBp0iQYGRmJHYWIiETQpUsXDBkyBB07dsTu\n3buxaNEitGrVSn7/t99+Q8uWLUVMWHEsWrRcjx49EBsbyxOdiYhqqPXr12PWrFnQ0dHB7t27MWTI\nEMTFxcHd3R2nT5/G0aNHcfLkSbFjVgjntGi5P/74A4sWLcLIkSPh5uYGXV1dhft9+vQRKRkREYkh\nKSkJCxcuRGJiIho1aoSZM2eiR48eYseqEBYtWu5NS50lEonGjGMSERGxaCEiIiKNwNVDREREpBFY\ntGipnj174vHjx/LHS5YsQW5urvxxdnY2XF1dxYhGRESkFA4PaSkdHR3cu3dPfpKzqakp4uPj5auI\nMjMz0bBhQ85pISIijcGeFi3171qUtSkREQFAYWEhrl27huLiYrGjVBqLFiIiohogPz8fo0ePhpGR\nEd577z2kp6cDACZNmoRly5aJnK5iWLRoKYlEonDO0MtrRERUM33zzTdISEhAZGQkDAwM5Nc/+ugj\njTgsEeCOuFpLEASMGDEC+vr6AICCggKMHTsWtWvXBgA8f/5czHhERPSO7du3Dzt37kSHDh0UvsS6\nurrixo0bIiarOBYtWmr48OEKj/38/Mo8x9/f/13FISIikWVlZckXZ7xKJpNpTE88ixYtFRgYKHYE\nIiJSIx988AEOHTqEiRMnAvi/KQMbN27E//zP/4gZrcJYtBAREdUA33//PXx8fJCUlITi4mL89NNP\nuHLlCmJiYnDq1Cmx41UIJ+ISERHVAB07dkR0dDTy8/PRpEkTHDt2DFZWVoiJiUGbNm3Ejlch3FyO\niIiINAJ7WoiIiGqAw4cPIywsrMz1sLAwHDlyRIRElceihYiIqAaYM2dOuUe3CIKAOXPmiJCo8li0\nEBER1QDXr18v96BcFxcXpKamipCo8li0EBER1QB16tTBzZs3y1xPTU2Vbzyq7li0EBER1QB9+vTB\nlClTFHa/TU1NxfTp09GnTx8Rk1UcVw8RERHVAI8fP4aPjw9iY2PRuHFjAMCdO3fQuXNnhISEwMzM\nTOSEb8eihYiIqIYQBAHHjx9HQkICDA0N0aJFC3h4eIgdq8JYtBAREZFG4Db+RERENYRMJsOpU6eQ\nnp6OwsJChXuTJk0SKVXFsaeFiIioBrh48SJ69uyJ/Px8yGQyWFhY4OHDhzAyMkL9+vXLXVmkbrh6\niIiIqAaYOnUqPvnkE+Tk5MDQ0BBnzpzB7du30aZNG/z4449ix6sQ9rQQERHVAGZmZjh79iyaNWsG\nMzMzxMTEoHnz5jh79iyGDx+O5ORksSO+FXtaiIiIagBdXV1IJBIAgJWVFdLT0wG82HTu5Z/VHSfi\nEhER1QDu7u6IjY2Fs7MzvL29MW/ePDx8+BBbtmyBm5ub2PEqhMNDRERENUBsbCyePn0Kb29vZGVl\nYfjw4YiKioKTkxMCAwPRsmVLsSO+FYsWIiIi0gic00JEREQagXNaiIiItJS7u7t88u3bxMXFVXMa\n1bFoISIi0lK+vr5iR6hSnNNCREREGoFzWoiIiEgjcHiIiIhIS5mbm1d4TktOTk41p1EdixYiIiIt\ntWbNGrEjVCnOaSEiIiKNwJ4WIiKiGubZs2coKipSuGZqaipSmorjRFwiIqIaQCaTYcKECahfvz6M\njY1hbm6u8KMJWLQQERHVALNmzUJ4eDjWrVsHfX19bNq0CQsXLkTDhg0RHBwsdrwK4ZwWIiKiGsDW\n1hbBwcHw8vKCqakp4uLi4OTkhC1btmD79u04fPiw2BHfij0tRERENUBOTg4cHBwAvJi/8nKJc6dO\nnfDXX3+JGa3CWLQQERHVAI6Ojrh16xYAwNXVFbt27QIAhIaGwszMTMRkFcfhISIiohpg9erV0NHR\nwaRJkxAREYFevXqhpKQExcXFWLVqFSZPnix2xLdi0UJERFQDpaenIzY2Fk2aNEHLli3FjlMhLFqI\niIi0WGpqKpycnMSOUSVYtBAREWkxqVSKRo0awdvbW/5jb28vdiylsGghIiLSYqdPn8apU6cQGRmJ\nmJgYFBQUwNbWFl26dJEXMY0aNRI7ZoWwaCEiIqohioqKEBMTg8jISERGRuLMmTN4/vw5nJyccO3a\nNbHjvRWLFiIiohrm2bNniIqKQlhYGDZu3Ii8vDyUlJSIHeutWLQQERFpuYKCAvz999+IiIhAZGQk\nzp8/DwcHB3h6esLDwwOenp4aMUTEooWIiEiLeXp64vz582jSpIm8QPH09ISVlZXY0SqNRQsREZEW\n09XVhbW1NXx9feHl5QUPDw9YWlqKHUspLFqIiIi0mEwmw+nTpxEZGYmIiAjEx8fD2dkZnp6e8PLy\ngqenJ+rVqyd2zAph0UJERFSDPH36FFFRUfL5LQkJCWjatCkuX74sdrS34oGJRERENUjt2rVhYWEB\nCwsLmJubo1atWrh69arYsSqEPS1ERERarLS0FLGxsfLhoejoaMhksjK75NrZ2Ykd9a1YtBAREWkx\nU1NTyGQyWFtbw8vLC15eXvD29kaTJk3EjlZpLFqIiIi02IYNG+Dt7Q1nZ2exo6iMRQsRERFpBE7E\nJSIiIo3AooWIiIg0AosWIiIi0ggsWoiIiEgjsGghIiIijcCihYiIiDQCixYiIiLSCP8fE8YyUh4r\niYgAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x113da6ad0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 前二十大流行电影\n",
    "popular_items_count_top_20 = df_items_sorted_by_mean_rating_merge.iloc[0:20]['mean_rating']\n",
    "popular_items_top_20_titles =  df_items_sorted_by_mean_rating_merge.iloc[0:20]['title']\n",
    "\n",
    "objects = (list(popular_items_top_20_titles))\n",
    "y_pos = np.arange(len(objects))\n",
    "performance = list(popular_items_count_top_20)\n",
    " \n",
    "plt.rcdefaults()    \n",
    "plt.bar(y_pos, performance, align='center', alpha=0.5)\n",
    "plt.xticks(y_pos, objects, rotation='vertical')\n",
    "plt.ylabel('Mean Rating')\n",
    "plt.title('Most popular Movies')\n",
    " \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>item_id</th>\n",
       "      <th>mean_rating</th>\n",
       "      <th>rating_times</th>\n",
       "      <th>title</th>\n",
       "      <th>release_date</th>\n",
       "      <th>video_release_date</th>\n",
       "      <th>imdb_url</th>\n",
       "      <th>unknown</th>\n",
       "      <th>Action</th>\n",
       "      <th>Adventure</th>\n",
       "      <th>...</th>\n",
       "      <th>Horror</th>\n",
       "      <th>Musical</th>\n",
       "      <th>Mystery</th>\n",
       "      <th>Romance</th>\n",
       "      <th>Sci-Fi</th>\n",
       "      <th>Thriller</th>\n",
       "      <th>War</th>\n",
       "      <th>Western</th>\n",
       "      <th>ranking_rating_times</th>\n",
       "      <th>ranking_mean_rate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>408</td>\n",
       "      <td>4.491071</td>\n",
       "      <td>112</td>\n",
       "      <td>Close Shave, A (1995)</td>\n",
       "      <td>28-Apr-1996</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/M/title-exact?Close%20Shave...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>305</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>318</td>\n",
       "      <td>4.466443</td>\n",
       "      <td>298</td>\n",
       "      <td>Schindler's List (1993)</td>\n",
       "      <td>01-Jan-1993</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/M/title-exact?Schindler's%2...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>34</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>169</td>\n",
       "      <td>4.466102</td>\n",
       "      <td>118</td>\n",
       "      <td>Wrong Trousers, The (1993)</td>\n",
       "      <td>01-Jan-1993</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/M/title-exact?Wrong%20Trous...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>286</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>483</td>\n",
       "      <td>4.456790</td>\n",
       "      <td>243</td>\n",
       "      <td>Casablanca (1942)</td>\n",
       "      <td>01-Jan-1942</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/M/title-exact?Casablanca%20...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>74</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>114</td>\n",
       "      <td>4.447761</td>\n",
       "      <td>67</td>\n",
       "      <td>Wallace &amp; Gromit: The Best of Aardman Animatio...</td>\n",
       "      <td>05-Apr-1996</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/Title?Wallace+%26+Gromit%3A...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>483</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>64</td>\n",
       "      <td>4.445230</td>\n",
       "      <td>283</td>\n",
       "      <td>Shawshank Redemption, The (1994)</td>\n",
       "      <td>01-Jan-1994</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/M/title-exact?Shawshank%20R...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>46</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>603</td>\n",
       "      <td>4.387560</td>\n",
       "      <td>209</td>\n",
       "      <td>Rear Window (1954)</td>\n",
       "      <td>01-Jan-1954</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/M/title-exact?Rear%20Window...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>106</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>12</td>\n",
       "      <td>4.385768</td>\n",
       "      <td>267</td>\n",
       "      <td>Usual Suspects, The (1995)</td>\n",
       "      <td>14-Aug-1995</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/M/title-exact?Usual%20Suspe...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>55</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>50</td>\n",
       "      <td>4.358491</td>\n",
       "      <td>583</td>\n",
       "      <td>Star Wars (1977)</td>\n",
       "      <td>01-Jan-1977</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/M/title-exact?Star%20Wars%2...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>178</td>\n",
       "      <td>4.344000</td>\n",
       "      <td>125</td>\n",
       "      <td>12 Angry Men (1957)</td>\n",
       "      <td>01-Jan-1957</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/M/title-exact?12%20Angry%20...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>263</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10 rows × 28 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    item_id  mean_rating  rating_times  \\\n",
       "15      408     4.491071           112   \n",
       "16      318     4.466443           298   \n",
       "17      169     4.466102           118   \n",
       "18      483     4.456790           243   \n",
       "19      114     4.447761            67   \n",
       "20       64     4.445230           283   \n",
       "21      603     4.387560           209   \n",
       "22       12     4.385768           267   \n",
       "23       50     4.358491           583   \n",
       "24      178     4.344000           125   \n",
       "\n",
       "                                                title release_date  \\\n",
       "15                              Close Shave, A (1995)  28-Apr-1996   \n",
       "16                            Schindler's List (1993)  01-Jan-1993   \n",
       "17                         Wrong Trousers, The (1993)  01-Jan-1993   \n",
       "18                                  Casablanca (1942)  01-Jan-1942   \n",
       "19  Wallace & Gromit: The Best of Aardman Animatio...  05-Apr-1996   \n",
       "20                   Shawshank Redemption, The (1994)  01-Jan-1994   \n",
       "21                                 Rear Window (1954)  01-Jan-1954   \n",
       "22                         Usual Suspects, The (1995)  14-Aug-1995   \n",
       "23                                   Star Wars (1977)  01-Jan-1977   \n",
       "24                                12 Angry Men (1957)  01-Jan-1957   \n",
       "\n",
       "    video_release_date                                           imdb_url  \\\n",
       "15                 NaN  http://us.imdb.com/M/title-exact?Close%20Shave...   \n",
       "16                 NaN  http://us.imdb.com/M/title-exact?Schindler's%2...   \n",
       "17                 NaN  http://us.imdb.com/M/title-exact?Wrong%20Trous...   \n",
       "18                 NaN  http://us.imdb.com/M/title-exact?Casablanca%20...   \n",
       "19                 NaN  http://us.imdb.com/Title?Wallace+%26+Gromit%3A...   \n",
       "20                 NaN  http://us.imdb.com/M/title-exact?Shawshank%20R...   \n",
       "21                 NaN  http://us.imdb.com/M/title-exact?Rear%20Window...   \n",
       "22                 NaN  http://us.imdb.com/M/title-exact?Usual%20Suspe...   \n",
       "23                 NaN  http://us.imdb.com/M/title-exact?Star%20Wars%2...   \n",
       "24                 NaN  http://us.imdb.com/M/title-exact?12%20Angry%20...   \n",
       "\n",
       "    unknown  Action  Adventure        ...          Horror  Musical  Mystery  \\\n",
       "15        0       0          0        ...               0        0        0   \n",
       "16        0       0          0        ...               0        0        0   \n",
       "17        0       0          0        ...               0        0        0   \n",
       "18        0       0          0        ...               0        0        0   \n",
       "19        0       0          0        ...               0        0        0   \n",
       "20        0       0          0        ...               0        0        0   \n",
       "21        0       0          0        ...               0        0        1   \n",
       "22        0       0          0        ...               0        0        0   \n",
       "23        0       1          1        ...               0        0        0   \n",
       "24        0       0          0        ...               0        0        0   \n",
       "\n",
       "    Romance  Sci-Fi  Thriller  War  Western  ranking_rating_times  \\\n",
       "15        0       0         1    0        0                   305   \n",
       "16        0       0         0    1        0                    34   \n",
       "17        0       0         0    0        0                   286   \n",
       "18        1       0         0    1        0                    74   \n",
       "19        0       0         0    0        0                   483   \n",
       "20        0       0         0    0        0                    46   \n",
       "21        0       0         1    0        0                   106   \n",
       "22        0       0         1    0        0                    55   \n",
       "23        1       1         0    1        0                     0   \n",
       "24        0       0         0    0        0                   263   \n",
       "\n",
       "    ranking_mean_rate  \n",
       "15                 15  \n",
       "16                 16  \n",
       "17                 17  \n",
       "18                 18  \n",
       "19                 19  \n",
       "20                 20  \n",
       "21                 21  \n",
       "22                 22  \n",
       "23                 23  \n",
       "24                 24  \n",
       "\n",
       "[10 rows x 28 columns]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#去掉评分次数<20次的电影\n",
    "df_items_sorted_by_mean_rating_merge2 = df_items_sorted_by_mean_rating_merge[df_items_sorted_by_mean_rating_merge.rating_times>20]\n",
    "df_items_sorted_by_mean_rating_merge2.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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jWoAAcRYYAFxY7GkBAACuQGgBAACuwMdDwCWGj54AuBWhBUCuIRABcBKhBcBFz8mDngG4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\nmAKIpwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11b2a5750>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 前二十大流行电影\n",
    "popular_items_count_top_20 = df_items_sorted_by_mean_rating_merge2.iloc[0:20]['mean_rating']\n",
    "popular_items_top_20_titles =  df_items_sorted_by_mean_rating_merge2.iloc[0:20]['title']\n",
    "\n",
    "objects = (list(popular_items_top_20_titles))\n",
    "y_pos = np.arange(len(objects))\n",
    "performance = list(popular_items_count_top_20)\n",
    " \n",
    "plt.rcdefaults()    \n",
    "plt.bar(y_pos, performance, align='center', alpha=0.5)\n",
    "plt.xticks(y_pos, objects, rotation='vertical')\n",
    "plt.ylabel('Mean Rating')\n",
    "plt.title('Most popular songs')\n",
    " \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 评分次数与平均评分的相关性\n",
    "散点图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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I0QWuRJY5+A5Umj1QE44KwJx5NRarOJPVWHHgmciXXc+dzp8/j6lTp2LFihXI\nyMhQPHbp0qUYP348Zs+ejQEDBmD27Nm49dZbFWe+I0mgANsMFbVNeHNnuanPYYM5W8YoeWDElXh1\ne1nIA2yJ1Nkq+rZG0/2kc/Wz7/VDQmyM8P2kfX0LiuWDaJGOstRBDEQKMKV2ajEhLwc7nh6Lvz16\nPdITlWf3Z6z6HBu+aH8dBcUVuHHJZkxZsQtv7CyXnamtuPgDqPT6JZ6POXN1Eaas2IUbl2wWuq/0\nWl5+aBicad4dv7Sk9tfle81VerQtmHPo+zmSAqnvXxyQKD19XuhxpA6rloAhFKTOTU2j2GdWqeMt\nnZvJQ7ojv2+W7CCBtIY4I0lfxkkwRXCkbdrWFp1AYWkV2mTSaURmkRd8WCJ7fyPomUk0u23SgJXc\nWTfjd4czr8YKx3tIJMcK37VEInQF2U8++SQmTZqEcePGqR5bWFiI2267zeu222+/HZ9++qmep7aU\nrV+cCncTAspI0peg4MalTqjUsVzz+QnMWSM2Y6XHn3fKp0SHlvYZwN/dmYt9R896FQ4S9Yt/HMDO\nI2cC/ggY0UGUAszsVOW15tIsqGc7Yuw22O021SDK5QaeWLkfizaU4Gfv7BcuFOYO8Jy+pEDO9zEr\nNQTpwKVBg1XTR+HFB4bgb49eLzso4vvjLBek56Ql4KdjesMG/6tGac9uacBAbX2xb4dV9HqQtgNT\nCwb18P0+EHlk6XUM75lhSLsm5OVg95xxyEyOU3zOjCQHnD7XvTMtQdfMhpaBnlANhigF/XpnEs0c\nqFEasDKrAjBnXo0VjveQSI7VBp6J5GiOxlavXo39+/dj7969QsdXVlYiOzvb67bs7GxUVsrv4dvc\n3Izm5ktrj+vq6rQ2MyQ812BbyY/ye+Hvn32rK9V1b1k1vqo8h1V7jgmt/w5Wrcn7Y4u6MjNR+Nj0\nRAcW39u+VdraohO6nq+hpQ1TX9+N9EQHHhndCzPG9te8HljtuAl5OUhJcHilRPuSfoxe2Pg1Rvfr\n2hHY7TzyndgLAbDikzLN15lSqqbIKPWcNQcxdkA24mLVxwk9U3ILS6sUB0V800iVUpqHXpkhtKZY\nLq0tkEAdVtHrwaztwAKtexN117U5uPn5LYYV94qLteMPd+fhZxdTxwMVTVt0zyDDKlNrSUcMZnBM\ntGq82nrvYJc5eC5RMHKtuNkVgH3bO7xnBvfPNRirOJNVMFOFIoWmIPv48eOYOXMmPv74YyQkaCiu\nZPP+cXa73X63eVq0aBEWLFigpWnkobXNjSE90vFRrfxAhpw3TE5J96Sl6rKZbUhLcuCNHeXC91k+\ndRhG9+sKIPiZkJrGVryw6TCgKkNPAAAgAElEQVT+/Gl5xx7n2rc4knfmvNhAybItRzr2Wgf8U6mV\n6J0wlfsBFEmXr65vxahF/8YfPNaTS5QCBD0/znLrZkXWFCsNGAQSqMMqGjhp3Q5MhJYBAk/piQ7c\nP+IKvLbdfwAm2HaJdvbl1tqKBJB61sHrHRwTLZQmGvSrbQ+m1jYzqtibWQFYrr13XZuD17aXcf9c\nA5lRrI9IK2aqUKTQFGTv27cPp0+fxvDhwztua2trw/bt27Fs2TI0NzcjJsY7FdPpdPrNWp8+fdpv\ndtvT7Nmz8Ytf/KLj33V1dejRo4eWpka15VtLw90EIVYIsN2QAkqxoDInLQGj+lzqvBtVfb2mobWj\nozw+14kHRvTAC5sOB2wzIN5B1PojE8q18cFun1Vd3+IXrKkFCEb/OMsF4FIgt/PIGaEZ4Bm39MXo\nfpd1dFh9A8F5kwbiyZWfB70dmJYZSq0DBJ5evH8InpFJKzeiWJvezr5oAKmncJaewTHRwFlL0D8h\nLwfLHxyKuWuLvWojKG1/KLXtbH1LwK0fgxkYMbMCsNL5e217GR4b0xvrDlRw5tVARhfrI9LKyIkI\nIjNpCrJvvfVWHDzovT73kUcewYABA/D000/7BdgAkJ+fj40bN2LWrFkdt3388ce44YYbZJ8nPj4e\n8fHG71tstLcevM6yKeORIi0xFrWN4UkZz06NR9MFl3BgaYN/cOtZxTpYbgDPvH8Q89eVyKY0a+0g\nnq1vMWRvcaOlJzlkfwC1DgxIwcXGkkrVgGV8rlPzj7PW1Fk96dX9s1O8tusKFJQEChi0bAdW29ii\naYZSJKNAzqx3DyjucGBEdWetnX0t6d96Mx607P+tJXDWEvTXNrZcXDpw6brITI7DvcO64/VPyjqO\n923bb+4YgLlrjR0YMbMCsMj5W3egAtt+dQv2HT3LmVeiTkLrdy1RuGgKslNSUpCXl+d1W3JyMrKy\nsjpuf/jhh9G9e3csWrQIADBz5kyMGTMGS5YsweTJk7F27Vps2rQJO3bsMOglhM/3BmcDK8Pdisj2\nk9G9A87YmqVLfCwWTr4GzrREuNxuxfXKnpSCkQl5OXhsTG+s+KQs6GBWaVZ91rirMGNsP00d3ECz\nUlZQ09CKjSWVAc+n1i3IKmqbsKu0Sjhg0fLjrDV1Vm96tTSwoDYzt/zBYchIjtO8HdjGkkr8eWe5\npmAnmPVsolsIhmrNnJaAFgDOnBNbZuE7IKRl3aqWwFn0PMm9z2frW/D6J/Izu3ddm4Pffliief92\nJWZvPSd6/vYdPcuZV7Iso+sfRAvWCKBIoHufbDnHjh2D3X6pGNENN9yA1atXY+7cuZg3bx769u2L\nv//9751mj+zyxZNCto1XZyLNGPbvlhLS5z3ffAHOtETk980SLlo245Z+mDX+KtkfvoLiioBrT41k\nA7B67zHMGNtP6PhgUn1DQamDrSc7oPAb5bRszwBB9MdZLuCtkAlM9Zxzz5lzkaBk4foS7Hh6bMc5\nKyytEnqeD4pOag52QrGezajnUOuoigZkyzYfweq9x1Rn8JXSEUVT2bXMloueJ7X3OdDMrlyKuFJ7\nRJi9VzWLH1GkM6P+QTRhjQCyuqCD7K1btyr+GwDuu+8+3HfffcE+lWWVL56ErV+c8kodz4gF2mJj\nkJkUh5F9smC3ASdqmnBlZiL+fei0oZW742NtaL4Q3nDqjjwnCkurvLZ9Sk9yoKahVXbGcN6kgVi4\nviSUzQTQPtuT3zdLuOM6ul9XU9ataqG1QxpMqq9e6YkO4b2T1V6PFAjPWXNQcXbtErEfVanDrfbj\nrPa+StuQeQamWs+578x5YWmVKeuAM5IdulK3jao3oOSsQruMqrgNtH/mRbyw6WvVY0TSEUVS2bXU\nBzDyffac2W1zuXHjks2a3l/RdmsNgrXO6LH4EUUyM5dSRBPWCCArM3wmO1p9b3A2ygdPUj2usLQK\nf9t93NDnDneADQAPXd8Tyx4c5tdJ2lhSKTtjmJYYF/JAEADe3FmOkb0zda3P9SUaWN2Rl42PioPf\nV93KszfLpw6D3WbD6XNNKCiuxEfF6oGN2l7fYwdkY9Sif8sGD9J7lN83S3X/acC7w6304yzyvvoG\nplrPeVqSo6OivJb7a10HfPeQ7kK7Bvg+v9pjG/GtM+eDg7g9zz+bwciK2+Nznfig6KQBrW1nVDqi\nluI9Zr3PWgaGtBYT0hIE65nRC1fxI6b3UrDMXkpBRNagvsksGaqzpq499e6BjhniyUO6I79vFmLs\nNkzIy8GOp8di1fRRePGBIVg1fRR2PD0WE/JywnYupB8woH02SrrN9xjp70o/cqKvYUJeDl55aFjH\nFll6WXH2xoZLVdfz+2bh+4MvxyeHzwjdV62d0r7INii/R6P6ZCEnLUF2Pltqo2iHu7K2UfNxWs95\noiOmYw2wlvvLrQN2pnnf7kxLwMsPDcM4j+dQ0jXZv9ik0mPPGtdf6HGV1DS0YpdPyrsUOPsGf1Lg\nXFBcAUC9oyplG+wqrRJeI65m3qSBHd9fwZICZ0Ds+8eo99nz+tH6HaylmJAUBKt9Js9e3CVA7f32\npfX8GaGguAI3LtmMKSt2YebqIkxZsQs3Ltks20aiQLQspSCiyMWZ7BDrrKlrp+rkU5zkZgzDdS70\nrM+VU/ZdvdBzdk2Ox+j+XTE+14llm4/glW1H0Njq8jrGZgPcKlvsiAaJoUj1lbjh3ZndVVqF883q\nFeMzkmJlX480W1RR04jPj5/FmP5Z2H+8Buea2jqO8X2PfndnLh6XWccttRFozyZRm4USDco8j9N6\nzo3YAkqilP7e5nIjJy1BdcbyqXcPYP5d/te83GO3udz4S2G5YDq/vMJvzmB0//Z9542suA20n+PC\nb8QGfER0TYk3NGjT+v0j8j5ruX5Ev4O7xMfgf/7PtZoGF0Rm36UlQ3pn9EJZ/IjpvWQUK2ekRTJm\nmZDVMMg2WcsFF94uLMfR6gb0zEzCg9f3DFnwE0qBKvSqfdmFMhAMZOeR7zra51sMaHjPDOw7ehZr\ni07Itr/N5cZfdx0VezKPux45XecXYAPKATagbVZGqYNrNtGgJr9PlvAaW4nNBtxy9WWYflNfzT+g\nnx87K5ySmp4UJ/SYmV0uzf7qKdgWzBZQvjwHs3w7G98f7MSKT8oV26JloEx6j+QCbG3XnPYCZVoq\nbpcKDoSJMGNgUGvxHrlBSz3Xz8jemXCmxqvWCElJcHhlXYhSC4LVlgyJ1KIIRfGjaE/vZfBiLCtm\npEU6FpEjK2KQbaJFG0r8tnV6bsMh3DqwW1jWInuSipIZSeoQLd30Nf6571vVLzu9gWCCw46mAEGq\nVsu2lPq1b/KQ7igorsDNz29Rbf+esmrhGc8z55tRUFyBZ94/qHreffe11jsrI9fBNZp/B1Os89Xn\nMv/K8mpbYLndwOb/fIf+3bp4dbqlTrCSV7eX+d0WaBaqoLgCz204JPQanKmBU7dFC7YFswWUnECd\nDZH+sGiwILJNmTMtAfdfdwWW/lt9nbzn+2hGxe3th79Dl3g7zjcH952hZbmBVoECZz2Bjdz1k50a\njykjr0TzBRcKS6s6HivGbsOUkVeqbqMYTBVwpSBYdIcHtevC7OJHZldKtzIGL8YLVz2BzopZJmRV\nDLJNsmhDScBOvcsNbCw5HYYWeUt0xODJiX3x3Ib/GP7Yf9zs37GW+7LTGgjaAEMCbLn2PTamd8Dt\nuAK1X0sqV/mZBizd9LXQQILL3Z5G2TUlPuhZA98O7uFT54UKhGnh28EULUIWKKgQrdS+4pMy/Hzc\n1Sg6XoPT55pw5lyzroEE38ByY0ml8D7X6YkOuNxutLncXu+PloJtoqnfIpkVgHxnQ3T/drVgQeQ9\nio+147/vHYzr+2ThrcKjioNKGUkOjOpz6Xm0VtzOTHaoDmbUN7cp/l3UXdfmhGz2rqC4AvPXfek1\nw+xMjcf8u65R7Sz6Xj/lZxqwas8xr0DaM0jq1TVZqE3BpK4Gu2Qo3DN60Zrey+DFHMFmLdEl0Z5l\nQtbGwmcmaLngChhgW0lFbRNqBbdbMoJUiGjOmoNY8/kJFJZWoe1iz9+zONrYAZcpPk5SXIyp7Vvx\nSeD9rqXbFnxY0tFuLR2/V7eXakrZ7poS71VALhhSB3fykO4Y3a9rUI+lROpgjuqTpVrgzTe4ArRV\nOna5gZF/2NRRgGjherGZ50CkwHJXaZWm7dhqGlsx9fXdGL34336Fj0QLtqmlBE8e0h21jS24+fkt\nqsWWjNxOTi5YEHmPmi+4MO3NPbj5+S24/7orFI9ddM8gv/Rl0QJ2MXYb7h7SXfHxjbTuQEXHZ99M\nBcUVePyd/X4p3JV1zXhcoRCYJ+n6iY+1Y+mmr1FZJ19UTPR77PCp817f20bQ8n6HU6QMBhhJLXgB\nvH8PSRu1QoYcvBDDInJkZQyyTTDk9x+HuwmCQj+qV13fill/9w8UpE7hmz8eiZ+O6e2X3mq3AXcO\ndqK+xZhZKTlK/QXpy/qtnWVYW3QCLrcbzlT/isyBNGhst1mdNWn2zwxSm2PsNiy+Z5Disb7BFaB9\nFuhck3pxNS0KvzmjazZcLvgxohMlWmkbMHZvdLnrT8t7VFnbhNe2l+GnY3r7pdXnpCXgFZm131oq\nRotW1DZCKDpqbS43nnn/oOIxz7x/UCiwEQ2ShvfMUAx0Jcu2HDG8mnY4KoTrESmDAUZi8GI+pd1X\nSEy0ZplQZGC6uMFGPLtRc0AVLvl9s/De/m/Dtj5cChSWPzgUGcnxHamxv54wEE/dNsCrYNy0/F74\nqLgCH36hvveyrxE903H4dD1qDJq595w1NWNmPTk+JmAashqRNZwxdhuenZyHJ1Z+blh7A6U+S1uW\nzV9X4jWLprSWL/yzQMF15J/6RxEOnqiFDUB+n64Y1TcrqKJMWtPgjOhEqK0F1PIeSW1cd6AC23/t\nXVhQ6RxoWZce6uKJlbWNQtXp9dpVWqVas0Ha9kyqyC5HNEjad/SsptoYRqcKh7JCuF7RmN7L4CU0\nzK4n0NlFY5YJRQ4G2QaqPt+C784bsx+r2dIvpusqbXsUiNTBiIuxoaUtuG6tdO8Zqz73mkFOT3Tg\nkdG9MGNsf69Oi94vye4ZSdh7tCaIlsozY0ClvrkNU1/fram4jJbiNBMHX46ffltjyJIGpQ6m1gAz\nXNXmpcBSdC25nPoWF5ZfLKa3bEsp0pMcWHzPIEzIy9HVidJabCnYToRIsDCydybSEx3CA1aegZyW\ncyB67YS6iv7C9Ye81tkbXQBKtDK/57ZncrQESZOHdBeujWHGOsdQVAgPViQMBogSGZBl8EKRgEXk\nyMoYZBvogdc+DXcThEk/pxPycvC9q7pi69dinbuMZAfuHtId9S0XsHrvt4a0xTfzsaaxFS9sOow/\nf1reEaQA+oOwnHTxToD94l7VVlhlJjpjpKc4zeyJubj2igzMXVssVCHdBuCa7qk4WdPoVWjKs4Mp\n13ETDa70bIElIictAXddm4PXLg4qyM1CjeqTZWiQX9PQisff2R8wLVqE1pkkkc+Hb+V6T9J7OT7X\nKTtbG2O34ZHRvVSrUet9LZ5Erx09VfSlwoJdk+Px1LsHcKpO7D33/awYXwBKNKhUP05LkNTmciMt\nMQ6/njAA1eebUVXfjD9t/Ub2PmZU046EGb1IGAwAlINo0QFZBi8UCaIxy4QiB4NsA50+Fxmz2ABw\ntqG1o4N0U//LhILspLgYVNe34o2d5eY3EO1BimcHVk8Qlp4Yi8wksXXTADD9pvbq4qHeWzoQ6fnn\nr/tSdsYomMqaEwfn4Pa89g5jZV0Tqs83IzM5Ds60RAzpkY6Vu49i++Ez2H/sLM41XUDxiToAQGZy\nHH4w5HKMz3V2dN6M2ubFqG3HPKuzS5W5L7S5sabohOwgAQBTZkWV3j8lWmeSRDoby6YMQ0ZyHE6f\na0LX5HjA1r69nNQR31hSiRuXbFZ8H2eM7Y8/f1quaQtAtdcS7D68UvCzq7QKT67cLzvTLgUGPx7d\nu+Px59+lf2DH6FldvZX5AxENks7Wt/i95+mJYnUbojFV2OqDAUrfxQCEB2QZvFCk6ExZJtS5MMg2\nULeUOMPW/YaC1EHqlirWmQ/HWnM3gF/98wBuvqobEuNiOr5MZ7//Bc42qBe+GtUnCzWNYoMft1x9\nGWZPzMXQKzP8ts8Jp8q6ZizbfAQzx/XvuE0KSnYeUS7W5Vk52zO91Deouevay/06S90zErH96+/8\nOmRn61vw553lXgG2kdu8iGyBJcc3iAq053mgQQLP5zZ6b/HKumZdM356ZpKC6WyIvo9SYTuRrc5E\nZruMGqCJsdswun9XLL53UEfQHCgwmDdpoNe1Pz7Xqfieq20TZuSsrlSZX8u2Z3JEgqS7rs3Bkyv9\n30fR3zGmChsn2IEmQP0znJbk0DQgy+CFIkWkZJlQdLG53e5wT9ipqqurQ1paGmpra5Gamhru5siq\nPt+CYc9uDHczhK2aPgq1jS3C+wKHk80GPHZTb8ye2D4a//y//tOx/tVIrzw0DAD8CnZZgZR2HCgo\nUZOe6MDiewfJ3t83qGlzuf1mtzxJwdO2X93iF8QGOm7H02M1/dgVllZhyopdwsdLzwWgIxiU63D6\nHhfIhwdO4v+uMq443As/vBZ3D1PezioQ6TUAgYMkudegtcMu+n57vo9q16FIG5dtPhww9VzkPVIi\nd43fdW0O1h2oCHjtSx0036yOyromzPp7kepzvvjAEEwe0j3oYEnawkuO1uUHcudi3qSBWLj+kK7B\nJL2fawrMiIEmtc+wqFXTR/kNFhkxAECRjdcARTO9cShnsg10+9Jt4W6CsPREBy60uTB/3ZeWD7CB\n9nXSUqGu2RNzYTNh+zEb2rfHqW1oteQ5WfBhCVwuBJx5UlPT2J56/9iY9nR4tdlK0aJbbxeWayrO\nJUpPGmpGsgPPTs7rWB+uN42+zeXG79Z9qfn5lSxcf6gjE0MLvTNJWlNatRZZk9omBaYbSyrxQdFJ\nr8wDpTYWFFcoDmQFm4YdaFbjbH1LwM+OWsZFYWmV0HN2S0kwJFjSU5lf7fECzfDo3fItHKnCnbmD\nb1QmkFFb+AX67rV6irwROvM1Fiyjso2Iog2DbINEUmVxoD3omvbmnnA3Q7MVn5ThqdsGBF0JOhA3\noGmdaahV1DbhNx8c1D0A4Eb7+RMJPDeWiG2VdrS6Qeg4rUGzaBpqSkJsx37Z1fWtWLj+EOx2G9IS\n44SCxrd2lnWs3ZY6VXvKqjWnqas5W9+iu0BWKNLg9G7XI3W+8/tm4TeTcoXaKBdU+Ao2DdszMJBm\n+fQMumhZ26wniA/E6Pc8UJAk+p77VpMPdapwZ+7gBzMY6Muo9fHRuASgM19jwTJ6ORhRNGGQbZBI\nqiweyVxu4O3CckzL74Xk+BjUN0fGnuSB6CmudTbIQQC5ytKA9/rtD4pOCj1ez8wkoeNEOm6eMwld\nu8TDmRqPU3XNiudICrAl0g//I6N7CbXLc89zqVPVaELtgWBnZs2eSQp2ux7RWSCloEKOEcGDnpl6\nicja5vbUa2OCJc/ntcJ7vnzqMNhttrDM8HX2Dn4w16UvI7bwi8Zq4Z39GguGkYNARNGIQbZBIqmy\neKR7b/8JvL6jLKIDbKC9Q/PAiB6at0MyW+E3Z4RmcjOTHZiW3wt/3HJEMQMgM9mB4T0zAv5NCs42\nlVT6Vf5Ov1ikR8tghHT8WsFBAk+VtU14/J396BJvzteiWoc5nOmKItt/pSc64HK70eZye7VLyyyQ\nnpRWI2bW9M7US9TS9kUzJ4zc8ipYojP0o/pkhaUDHQ0d/GCvS08i72d6kgNnG1pZLfyiaLjGgmHk\nIBBRNGKQbZBIqyweyUoq6sLdBN1m3NIP/bO7dARRALB673HD9mY2gtJst6dRvTOxqaRSNcW+ur4V\nNz+/xS/oUiucVXvxcdNUqi37cgOoqm9BZrIDZ+vF19dLx51vVq9aH4xAHeZwpysqzdZKahpbMfX1\n3V7t0joLpGVW2siZtWBn6gHlFO61RSeEHt9KW15ZfYumaOjgG3FdSkTez0X3DAIAVgu/KBqusWAY\nOQhEFI3s4W5AZ7H6sRvC3QRCexVyKxvdrysmD+mO/L7ts0NSx8hKMpLihI7bUHwKMwQrcEtBV0Fx\nBYBLKXpqHRwbgERHDH5+a3/Z4+TcPaQ7AJhQIi84vh1muXPhe86M1uZyo7C0CmuLTqCwtKpjKytn\nmnKHXmrXhi8qFGeB3ADmrDmIlguujtu1zkprCfJ8X0+bx2jRyN6ZSE9S3vs5PcmhGtBLKdyen2HA\n2GAplKQZet/33JmWEPY02Wjo4Euzz3JXuA3tg22iA00i7+eEvBzseHosVk0fhRcfGIJV00dhx9Nj\noy7ABqLjGgtGpH6vEVkFZ7INktklDpd1iYuo4medkZU3pJPrxE/Iy8HyB4di7tpixf14g6El5bpr\nSrxq6rBEdNbbM/Vu7IBs4XW50kzCX3cdFXsiD+NynRjRO9PQPa9T4mMQE2PXVYE+0MxsuNIVA82c\nZ16szr7j6bHYVVqFJ1fuD5idI7Vr3tpiVKksK6iub8WoRf/GH+5ur/oukpYOAM7UeMy/6xrhjr8R\nmQDBnF09e5pbhVX3l42GDr4Z2QQi72c0VAsXEQ3XWDAi+XuNyAo4k22gvXPH47IuYrOAFH1qGlr9\nqna3udx4cdPXmP3+QdMCbABIS3TgvmHdhY51piZ0zK4b2c0W3fYrEC3Vvj1nfzxnbX4yuhdSEoIb\nV/z9DwZh8cWUS63nxg3/DrOWdEWjyM2cV9e34omVn+O/C9qLwSktf5FS8kVUX6ysXlBc4ZW5IXf+\nZo27CjufuVVTgK2WCbCnrFp1ycHZhlbd51npdVkh9VqN3Ax9OBk9y2tVZmQTWPH9tKJoucb0ivTv\nNaJwY5BtsL1zx+OpcVeFuxkhER9rzhdrgqPzXpbPvH+wI421oLgCw5/diBc2HUZtk7nrgGsaW/HP\n/Seg9FvoG5yKpA7rIbrtVzA8f/hj7DbUNrbgzzvL/aqRa+VMTdB9bjKSHBif6/S6LdTpiiLVvV/d\nXobpb39myPN5WvBhCdpcbtnzl5OWgFceGoaZ4/prShFXygSQnreytlHo8YI5z1ZOvY5E0dTBZwp3\neETTNaYXv9eI9GO6uMFqG1qx5atT4W6GsLhYu9eaSV/jc7uh+ESdXxrmvEkDkZLgwH/9ZS+a24zN\n0U6IjUFTq3ybIllNQyt2lVbhXHOr0F7BRlPbwmvepIEdHYoJeTkYOyAbwxZ+jPMGVnIX3fZLr8fG\n9Pb64dezbVQgnun+UkqmUlq1L2mm1DNNM9TpiqLVvRsEtzETLS7nW0DIqBRl0UwA0UyIYM+zVVOv\nI5VaVffO1MFnCnd4RNM1phe/14j00RRkv/zyy3j55ZdRXl4OALjmmmvw29/+FnfccUfA49966y08\n8sgjfrc3NjYiIaHzrXG5+fnNOFolNmNiFV3iY1F9Qb4DWnyiDpuf+h5W7j6Ko9UN6JmZhOyUBCxc\nf8iwda6+OnuV9p2l32HN5yfDWk3cbgsccM9dW4x9R89iXK4TI3tnYt/Rs4YG2HYb0C01QXjNt1Y2\nAOsOVODXEy4NFogGlmr7rkvp/lKnK8Zuw+j+XbH43kF4/J39Qu3znSk9KxD82W1ix+l5fr2ktXjz\nJg3EkyvFit/5Pr8RQYXo68nsolxnwMi1hUqvK5zbtEUqdvDJbLzG1HEQiEg7TUH2FVdcgcWLF6Nf\nv34AgL/85S+YPHkyPv/8c1xzzTUB75OamoqvvvrK6zYG2NaQ5LCrzvBU1DZh9JLNmtbEGiE90dFp\ng+2TNU2mDVCIkpvRrq5vxRs7y/HGznLkpCXgjjxn4AN9iBZWc7mB/2/V53hsTG+8tr1MU0E2EYG2\nXBENxH5/Vx4Wri+RXbsrV4RsQl4OZo3rL7TfuedMaZvLjYXrS1Tv43IDT67cj5ftw/xm6LV2Co0s\n4PO7O3MxPteJn487j9c++UZo33qjCwiJPp5UZyCc21WFe5u2SMYOPpmN1xgRGU1TkH3nnXd6/fu5\n557Dyy+/jF27dskG2TabDU6nWEc9UtU2tEZcgA2IV4Y2KsC+dcBl2FlaJZQK/sjoXli66bBl9o42\nUveMxHA3QUhlbRPe3FkudOzMW/vj+j5ZOH2uCd98V48/bj6seH2tO1CB5Q8Oxe//twSVdc0dt2cm\nOfCDod2RFBeLZVuOBNH2S59H0UCspqFFsThWoABeCnSvzEpGRpIDZxUCdGmmVLrPziNnNA22eAb4\negO2kb0zkZnsCKrIXnqiA4vvbS/+duOSzUKvwawqtFqq38bYbWFLC9W6nzgRERFFNt1rstva2vDu\nu++ivr4e+fn5ssedP38ePXv2RFtbG4YMGYKFCxdi6NChio/d3NyM5uZLHe+6ujq9zQyJn7y1J9xN\n0KVJYS22Gf79n++EjstOicN1vTLxk9G98I99x3Guybh05XDLSHLghr5dsXxLqfB9jJ7tFSVt1WST\nSS2XZCQ58H9vvVSsqrC0Ci/+W35WVwpWD5+uh2+5mbjYGIzsnYm0xLigguyF6w8hMS5GaNsoKRDL\n7BIv9Nivbmt/bZtKKrGm6IRqwOo5U7qxpFLXlmKeAX5tY0vAgK2itgmPv7Mfs8b1x4yxgYuHxdht\neHZyHp7QkOLta/nUYTjXJF5TwMyZYq1bIIUjLTRc27T5toGpsERERKGjOcg+ePAg8vPz0dTUhC5d\numDNmjXIzc0NeOyAAQPw1ltvYdCgQairq8OLL76I0aNH48CBA+jfv7/scyxatAgLFizQ2rSwORnm\n1N/Opr7Fhamv7+74t81m7f2vtbiuVwZqG1pl10QHEs6X7ob6ub+xn3eKnWh69gubvva77VRd+8ze\n8geHISctQXda/dmL20ZJM4QigVhaotj2e1u/rsLWr6uE25Jxcf9pAEEXu6usbcR//+srxcd4YdNh\nvPVpOe4Z2r1jbb1nQG2qaOcAACAASURBVDVx8OX46bc1eHV7mabnlgYjRvTKxM3PbxF+HWbPFGst\nXBTqtFAt27SZ0S6mqRMFxsEneTw3RMGzud3awpeWlhYcO3YMNTU1eO+99/D6669j27ZtsoG2J5fL\nhWHDhmHMmDF46aWXZI8LNJPdo0cP1NbWIjU1VUtzQ+LeP+3EvmM14W4GRQDpJ0pPoOUbmKcnOQBA\ndf/fUHCmJuC33x+IjOR47Dj8HZZvFZ+p9+VZVCuYGVfpcXY8PVYoxbrN5RZOf1bj+145UxPQdKEt\n6Pdq3qSBWLj+kKb7yAVUG76owNy1xV7LQdKTHKhpaJUdjHj5oWFIS4zDlBW7VJ93xi19MbrfZSHr\nnFm1U7i26ARmri5SPe7FB4Zg8hCxvexFyaWpS5SyHog6Mw4+yeO5IfJWV1eHtLQ0zXGo5iDb17hx\n49C3b1+8+uqrQsdPnz4d3377LT766CPh59D74kKltqEV1/7+43A3w1AZSbE422Du3s2k3bxJA9E1\nJb4jiADgFVicrW/BwvXa05GtaNX0UThb34wZqz4XnvWXexzfNdRygVhBcYVwpfBQy0x24DcTc/HU\nuwc03c8zQPbtIAU6H4FS2j07WOEMGiNRYWmV0KCE53VqBNFBI2dqAubfxc4zRQ+5wSel78powXND\n5E9vHBr0Ptlut9tr1lnt2KKiIgwaNCjYp7WUtCQHemYlRmTxs0C6xMciPjYGAINsq+maEu8XuPh2\nzG/P07Z/s1WdPteEyUO64yUXMGO1/hltLdtGTcjLwfeu6oqtX5/R/Xxmqa5vxXMbtM1iA8rrfgOd\nD7V1y6He2zvSaSnOZiTRresq61h8jaKHFWokWBXPDZGx7FoOnjNnDj755BOUl5fj4MGD+M1vfoOt\nW7di6tSpAICHH34Ys2fP7jh+wYIF+Ne//oVvvvkGRUVFePTRR1FUVITHH3/c2FdhAdt+NRY9syKj\narSa880XvCo+k3WIBC4xdhvsdptQgJ2Z7JD9W7h/QrulJKCguALPfRQ4sFRqu+/jaHFT/8s0HW+k\nO/KykZksvzZc737Znut+RUjB9+Qh3ZHfN8urQyUFjXLXhw3tM99GB42RSirOBvh/pswsCqd1T/QF\nH5agLZiUEaIIoKVGQrThuSEylqYg+9SpU5g2bRquvvpq3Hrrrdi9ezcKCgowfvx4AMCxY8dQUVHR\ncXxNTQ0ee+wxDBw4ELfddhtOnDiB7du3Y+TIkca+CovY9quxOPDb2zA4JzncTaFORmvgsrGkUui4\ned+/Bqumj8JPRvfyC+6caQkYN7Cb1qaqsqF9zbLS33PSEjqKl8n96C+4K08x2APaA/HhPTM0tW9a\nfq+wDDBkJjuw7MHh2DX7VtlAO9gQSGvgFUi4gsZIJhVnc6Z5D/g40xJMm0HWMrjEzjNFC9HvQCO+\nKyMNzw2RsTSli7/xxhuKf9+6davXv1944QW88MILmhsVydKSHHA4xGbYKPrEx9rRrHHrNK2BS5vL\njTWfnxB6bGdqAvL7ZiG/bxZ+MynXK0V4839OYcUn2ipQq5FaP/2m3njtYnXrQAW22gt8BU5bk477\nw4ZDmDdpIJ5c+bnsNmfV9a24+fktqgVbfNcm/+TGnnhjx1FNry1Ydw/pjhi7DXvKqoX2plfal1uO\nUSncWit6U+i3D1NLUw+EnWfq7LjcRR7PDZGxgl6TTf6OnjkX7iZ0St8flI3/PXgq3M2Q9YMhl+OW\nAd2wseQUNhys8CrWZbcBj97YC+/uO6EYZCc47IiPsaO26dJ6eK2By7LNR4SCr8xkh9fMuOf63JYL\nLkx9Xb1Yk1aer2XolRmyQVpaYpxQ2lpGcnzAYM9TZa3ymlO5SqqhrrMwLtcJQDzQ+e2d1+BYVUPA\nrdB8mbHuNxx7Tke6UG4f5rmHuCh2nqmzC1eNhEjAc0NkLAbZBrv5+c0409AW7mYAAGLtNlzoJGvs\nvndVV9w/oqelg+wrMpIweUh3TB7SHS0XXHi7sBxHqxvQMzMJ0/J7Yd/Rs1jxSbniYzS1uvDGj0bA\nbrPpClwKiiuEgi4AGNU7E//7xcmAz/F2YXlQFb0lNgCZyXGYO2kgnGmJXs+jFKStLRKbiZeKo40d\nkI1Ri/4dcAZYrmBLm8uNZZsP44VNh/3uE8rq7L4dF9FAx5magLuHdsfVzi6KgwxmpnCHes9p0kbK\nOJi/7kvFOhvsPLez6jZwZBzPwSe5rQqjdbkLzw2RsRhkG+jm5zdbqsL4BZcbkwY5sf6g2PpcK7up\n/2XYXVZl6GPGxdrRojF1W0laogNri050dM4evamP199FZyjPnG/WtfWRVBlU1IbiU9hQ3D5o4bsH\n5tHqBs3P70v6GX7u7jzZWXi5IE1r2tq+o2cVU6w915zm981CQXEF5q8rQWWdOcF0clwM6lsuDbap\n7T/t2XHROpvgOVixsaQSHxSd9DoXVk3hZkATGtL1sWzzkYADcOw8t+PewNGDy13k8dwQGYdBtkFq\nG1otFWBLxg3Mxn3DrsB/vf0Z2oyLJ0PKbmsvRvXSv/1nHPVKS4hBXbOxGQee2ysF6pyVnxELXPWm\nbIpu2ROIZ0r1+Fwn3G6xaewfDLkc94+4MuD+3MH8KIusJ/UsaqalYIvcPqBG+vHoXrix32Wq+08H\nOkd6ZhOkwYpAa+utGLwyoAmtGLsNM8f1D5j1wM6z/N7AaktNKHJxuYs8nhsiY9jcor3pMNK7CXgo\n3funndh3rCZkz+ewA60CQbPvjJqV2G0QSkn+6ZjemD0xF0s3fo2lBgbaZpJ+iqTOmUhgJ81Q7nh6\nrK4fs7VFJzBzdZGe5nY8f1qSAwmxMUIzvHYb8J+FdyAutn2TAs+Zya7J8YCtfVZe7w+0dM4A+ara\nztR4zL/rGqQlxmHKCvU15L+ZOBDLtxwxff/wv/3X9Rjdr6vf7VpmbztrICr3WfD9zJA5mEHgrc3l\nxo1LNisutwjme5mIiCKb3jiUM9kGORmiNZzSzJZIgA3AkgG21E1ZNmUYMpLjcPpck2yxsOk3tQfY\nBcUVeDFCAmzAex3w2AHZWPChfKVsz/sEk7IZbNEiN4CahlYAYgHo9Jt6dwTYwKXZ1ILiCvzynweC\nDg7l0tY8VdY14/F39uNPDw5Tnfm227yzDcySkeTAqD6B1ylrWcPcGWcTpCUNgd4jubXzZCyuo/em\nZW9gnjciIhLFINsgl6clhKRYUnZqPJouuC4GQ5EpUHqiXLGwuFi7YsfcyqTO2V8+LRO6NmaN6x/U\nDJ6eLXv0kCqlf+/qbK816DF2W1Bpl4Fm2Cbk5WDsgGwMW7gR55svBLwfAMz54CD+8IM8xe28QlUD\ncNE9gwwLEDtbQMSAhqyGewMTEZEZGGQb5M0fj8S1v//Y9OcZ3a8r3tsvVnnZamLsNjwzYQB+dEMv\nrxlQSVys3a9YWJvLjbd2igWpkrTEWNhsNtQ2tFoiMA9UvTqQKzOTUFha5RVkAtA0k/nAiB7Cz6fH\ntFFXYmTvLPxhwyGvSuk5aQmYNylXdm9rtVlKpdTolHiHYoANtM/ApyXGBZz5Fl2WoJXv40Z6Knco\n0ogZ0JDVcG9gIiIyA4Nsg6QlOUKyr26kBthAeyf+uQ2H8ObOMsVgpM3lxq7SKvxtdzm2HT6Deo0F\nyv40dTjONbVq2h/WTA2CKfsL1x/yqgqdnuQAAK+shcxkB+4e0h3jcp1eQVCgINUMjhg7/r9Vnwec\nqX5ipfL5lpulVJv9npCXLdS2wm/O4Je3D/BKsT5zrhkL1xuXIp6aEIv7hl+B8blODO+ZgX1Hz3aK\nVO5Qrf9mQBMeXIctj3sDExGRGRhkG2jdkzeFZDY70imlDhcUV+CZ9w/qTofPSUvAqD5ZiLHb8PJD\nwzBnzUFU10dGar3vFlSBzkF1fSve2FmON3aWdwRBAEyvli15d9+3sjPVojxnKUXW6H5yWHTrtvag\nwTPFWnS/bVELJufh7qGXtlfrDCnNoayszIAm9DprAT2jcG9gIiIyg3/OLun2k7f2hLsJEUHqxCz4\nsARtHvm2BcUVePyd/UGtN/fsDE3Iy8G871+j6f6pCbF48f4hyEnznklLT3Lg57f2x4ie6brbZjQp\nCHrm/YOaA2zf/qIzNR7pSQ4odSNtNuBck3LatgjPWUqRNbpqqeKSYPbbFuVM7VwzrGqDHID/5zQY\nUkADwO9aY0BjPGkAxfczJn13FBRXhKll1iIVWXT6fO870xJY7Z6IiHThTLaBQlVhvDPwTR1uc7kx\nf92Xuh8vLTEWS+4d7NcZ0hoU1TVdQLfU9u1afNMrN5ZU4q+7jupuo9GksEfPoITLDcybNBBdU+K9\nXl+g2ZyO5zMgznKmxnvNUoquvU2Ki1FMu5er6C1SDC49yYE/3j8Uv3rvC5yqi64Z1nAUIpOrGs/9\nmo3FSu7adMZq/kREFD4Msg0UqgrjnclfC8s61s5W1jXrfpyE2BgcqqhD8YlaAO3pwqP6ZGF4zwxk\nJjs0pYxX1jYGDLBDlZIdKpnJceiWkoDT59qDqPG5TtMLhzVdcGFjSWVHICU60/zTMX0UC7rJVfQW\nSQVdfM8g3HT1ZZh/lzVTRs1cTxuuQmQMaMzHSu7adbZq/kRmY70HInk2t9uI+Slz6d0EPNRqG1q5\nJttC4mPtiLHbhAuPSTKT47zWRztTE9B0oS2it00LxPd1Sus0jSgc1iU+BucDFKyTfnqlFMw2lxs3\nLtmsONPsTI3HzmduxcaSSsxfV4LKOu1rS0XXpVpt/arR7fHtELlcbkx9Y7fq/VZNH8XgI8KsLTqB\nmauLVI978YEhmDyku+pxRESerPZ7SWQWvXEog2yD3fz8ZtMrjBOZwTMAlgLtl7cexnbhwmOXpCU6\nUNsYeFBCSr3e8fRYr721gcBp6ulJDiy+Z1BHUK531FyqWl/4zRl4Zjv43l/0OLPJFSTzHajQ8nh+\nKdoXB5Dktrvzfa8ochSWVmHKil2qx3EAhYi0Mvr3icjKGGRbyIB5G9DUavnTSuTHhvbt6BJiY7xm\njM3g2blXqipv1I92JM1mSzP8cum+WoNfpQ6RO8D/S/8G2FmKVGpZIuEYQGFqKVHkM/r3icjq9Mah\nrC5ugs9+c1u4m0AUUGayQ/HvbrQXUtMbYNsApCcqP4fEc53v+FwnEmJjZNsEBFflWrTKstxxFbVN\nePyd/Xhx09eGVdpWomU9rRqRAlgZSQ5kp8Z7/c2qlZXbXG4UllZhbdEJFJZWheT9iERWq+ReUFyB\nG5dsxpQVuzBzdRGmrNiFG5dsZoVzoghj5O8TUWfGwmcm6JIQi+T4GNQHWJNK1vHE9/qif7cuWLj+\nkN8e1ZFAtKCbZxXxyromzPq7+jrNYDwyupdikTKJ71ZeSoF9MEWaRKssjx2QLXuc5IVNh7Fqz3HM\nv8vcWW0jC5KJdIjONrTib/91Pew2m+osYzhnI62QZRBJrFLJPZR7sRORucJVMJMo0jDINsk9Q7vj\n7V3Hwt0MUrB673H8KL9XRAbYWclx2PH0WIz9f1tV00F/PLp3RxBUWKp9fbUoz8Jpq/ceVwzscny2\nwzL6R9szEDxzrllo1P3twnKh3QEq68wPDESrroscJ3rOzpxvVi2AFc4gl4GaPuGu5M6txIg6FyN/\nn4g6MwbZJpkzMZdBtsWdrW/BC5u+Dncz/CQ47GhqdSkeU1XfgqLjNarbU/mmg4rsG61FakIs7ht+\nBcbnOr067nddm4NXt5fJ3u+ua3O82mXkj3agQFDE0eoGTcebGRiovU9a9u026tyGM8hloBaccG5N\nxa3EiDoXI3+fiDozrsk2SWJcDMbndgt3M0iBVVdyqgXYkp1HvuvY29qZ5h0gya2nVVqnqVVqQiw+\nmzsev73zGuT3vVR9u83lxroDyuss1x2o8FpLK/1oK7UpM9mB4T0zFB9Xbk21iJ6ZScLHmr3mzMj1\ntGrn1gb/zAJfakEuENyaeTVcAxi5mFpK1LlYrd4DkVUxyDbRiodHMNAm0yzbUoobl2wGAOx4eixW\nTR+FFx8YglXTR2HH02P9AmypYFTzBRd+Pq6/X6ErrRbfMwhxsf5fIWoBEeAfEIkE/9X1rbj5+S2y\nhZKUAkElUpA5Lb+XaqDvy8zAQFpPKzqAIseIDlG4g1yzAzUWUzMPU0uJOh+jfp+IOjOmi5tsxcMj\nUNvQimt//3G4mxJVUhJica7pgqb7+KZcq0l02NEoOOtsFtFUXbk9kmeNuwq9uibh8KnzWLbliPDz\n/nRMb0wcfHnAv+kNiOSKNHlSer0iwb0vzyAzLtbekX4vyuzAwKj1tMEWwAr3bKSZgRqLqZmLqaVE\nnVO46z0QWR2DbIOs3H4EczZ8Fe5m0EUP5/eEDTZ8e7YBHxSdVD1+1rj+qsW6fIU7wAbE1qPKrqWt\na8ILm77Go6N74fL0RKHnS02IxeJ7BmPiYPngI5iAaEJeDsYOyMaoRf8OWJBO6fXqCfB8g0wpGJ2/\n7ktU1jXL3i+UgYFR62mD6RCFezbSrECNxdTMJ2VSaKkdQUSRIZz1HoisTlO6+Msvv4zBgwcjNTUV\nqampyM/Px0cffaR4n/feew+5ubmIj49Hbm4u1qxZE1SDrajXM+tNCbDjYmxgv0Of5VtKsWzLEXxQ\ndBI2lXOYnuTAjLH9vVKuJw2KnI61UqquSAr1GzvLsXD9IdVrLSs5Dp/NHa8YYAPBrwHed/SsYsV3\nuderNcCbNe6qgGn1E/JysPOZWzFr3FWy7QciMzCQOkSTh3T3Wkevxoh13cEwYw1guNeZRxOmlhIR\nUbTRFGRfccUVWLx4MT777DN89tlnGDt2LCZPnowvv/wy4PGFhYW4//77MW3aNBw4cADTpk3DD3/4\nQ+zevduQxltBr2fWm/bYLW1usH8XPLfKOZS65VIA8v3Bl6PwG/O2ujJLoJlcLSnUctea7eJ/z92d\nF3ANtq9gAyK9qckixdM827F6r3z1/xi7DTPH9ccrDw1DDgMDSxS6MTpQE11nvqu0iuu1DTAhL0eo\ndgQREVFnYHO71UIQZZmZmXj++efx6KOP+v3t/vvvR11dndds94QJE5CRkYFVq1YJP0ddXR3S0tJQ\nW1uL1NTUYJprKKaIh15SXAymXt8DKz4pN/Rx500aiK4p8eiWkgCXy42pb0TeQNCq6aP80rbWFp3A\nzNVFmh7HbvMOuPWuT9W71rWwtApTVuxSffxAr1cu/VfLY/jy3HM72tecWWH9slHvh+hnIz3RgZrG\n1o5/c702ERFR9NAbh+pek93W1oZ3330X9fX1yM/PD3hMYWEhZs2a5XXb7bffjqVLlyo+dnNzM5qb\nL62HrKur09tMUzHADj27zYZn7sjF0B6ZmLu2WDGtWIuF6w91/H9SXIwhjxkqSutR9ayRdbm9Bx2k\nIEZrcKN3DXAw62+l2c6n//kFagUK34nMmnPN2SVWKHRj1Psh+tnwDLABrtcmIiIidZqD7IMHDyI/\nPx9NTU3o0qUL1qxZg9zc3IDHVlZWIjs72+u27OxsVFZWKj7HokWLsGDBAq1NoyhwvvkC9pRVY+Lg\nHNye58SyzUfwwqavDX2OhpY2Qx/PTGqpumoBq5yuKfGYPKR7x7/1zmDqCYiMKJQUEyO2EobbBmkX\n7kEHo2ay9X42RIoNEhERUXTTHGRfffXVKCoqQk1NDd577z386Ec/wrZt22QDbZtP1Sm32+13m6/Z\ns2fjF7/4Rce/6+rq0KNHD61NJQuZcUtf5Pfpil/8owinzslXbRbhOfuotK7W6pyp8Zgysid6dU1C\n1+R4wAacOd+M8jMNWLXnGCrrvAPau67NwboDFZq2YFIKWJV4Bp/hqMCsd8spLeni6YkOuNxutLnc\nDJQihJHp6no/G4B38T1mORAREZEvzUF2XFwc+vXrBwC47rrrsHfvXrz44ot49dVX/Y51Op1+s9an\nT5/2m932FR8fj/j4eK1NC7k/TLyaKeOC+men4FxzK5rbAm97pScA1LMvslXMGncVZoztJxvczRjb\nL+Bs3a8nDOy43TMwLyytkp3RE9l/WuKbiq1WgdnMGT2tqckildQ91TS2Yurru7nGNkKYMdgj99nw\nXYctx6x9wYmIiCiyBb1Pttvt9lo/7Sk/Px8bN270Wpf98ccf44Ybbgj2aS3hwTH9GGQL+ua7erz0\n78OyAVBaYizcAGobldfROlPjOwLAcHVwb7n6Mvyn8pzfbNq8SbnISI7rCAjP1rdg4Xp9s25yKbnS\n7QXFFfjlPw8IP7ZnwLqxpBJv7iwXSsUWrcBs1oyeltRkvYMuXGNrfWYO9gQazHG53Zj6unrxQy43\nICIiokA0Bdlz5szBHXfcgR49euDcuXNYvXo1tm7dioKCAgDAww8/jO7du2PRokUAgJkzZ2LMmDFY\nsmQJJk+ejLVr12LTpk3YsWOH8a8kTMoXTzJ1G6/OQinABoALrvb11mqmjLyyoxNdfqbBoNZp89iY\nvhjZO1NohvX2POOLROmd0ZMC1vy+WRjZO1MoFVvvdlrhoLcNXGNrfWYP9vgO5rS53LqL7xERERFp\nCrJPnTqFadOmoaKiAmlpaRg8eDAKCgowfvx4AMCxY8dgt18qOHTDDTdg9erVmDt3LubNm4e+ffvi\n73//O66//npjX0WYlS+epLqdV8L/3969h0dV3/se/0zIhRCTgYBhgqikSNUY7oIEKFoURJCq1V3F\na22P+2DBYrHditYNbJ8aabvrZVNptVa3ZQues1ELG0TwAEE0iAIRMF4QwkVMjNwmIZAEknX+SNeY\nSeay1mRNZpK8X8+T52kmv7XWb8KvbT7zu3xd0hlJZzppidVwb9tKwJakfr3SJDX+EbxkS9vvx05w\nSceq6yzPsDp9SJRTM3pWl2L3SrO2bcNqu2hqzawie2zjW1t/2OPE4XsAAKDzshWyX3jhhZA/37Bh\nQ4vXbrrpJt100022OtUe3TruAt067oKgP//Bwne048v4LEXWnjTdj930YLC20mBIM17ZpkUJsVla\n7OSMnqUPAKxmiDjIGpGeFt1UPMzIx7NY1Qy3+gGKk8u3Iz18DwAAoNV7shHe3OW7CNgOyG6yPNPJ\nMJTgagzPpu6pifLWnJERIqk5vbTYanhp6xm9wyesnQR/+ERtzAKYqTWnRZvYYxuckyd729Wa2umt\nEQ91wQEAQPtDyI6yx/6nRP/53v5Yd6NDaLo806kw5JK0cNowvwPLwh16ZM4Wb95zRAkJrlb/8W0n\nvLT1jJ7V++w7fFJjF6yLSQBrKujsY0aKas40yHvyNHtsIxCLMm5NxXL5dqzrggMAgPbHZRih5uvi\nQ2Vlpdxut7xerzIyMmLdHcsKVpXozxtLY92NDuEXVw3QrKu+6/u+vsHQ2AXrWrU0uEe3RP14dI76\n9UrzC8l/Lz6kWUuLw17fvMxPJKEyXF3nX1w1QDPHD/CFh3Dv2wyLmx4c70jgsPI8d7ekgOHVfHos\nTu0ONKu+tqRc9y7eJilwSON08cDMMRBqm0JmWpI2z7lKyYkJQds4IZaz6QAAoPOJNIcSsqOk7kyD\nvvvrN2PdjQ4hO0hoNAOqZH9p8FkpiTorJdFvX7f5x7o7NVnTnt9su592w5qV8CJJnoyumveDb0NE\nsPcdrbAY6nmGpO7dknT8ZOCawk6H/lCsLFcnpNlXtOeIpf8+ZKYl6/Eb8qL+e4z1tgQAANB5ELLj\nTO6/rtbJuvpYd6Pdcyl0aAwUmprvsW5+v2AD3vwz/ZlpQzVr6fag9wjX36ahMlQgsBpezPs2/T20\ndVgM9rxbRpyrJ9/eHfb6JfeMiuqSWzu/D0KaPVZXdkjh//sKAADQnkSaQ9mTHQVHT9QRsB2Q4JLu\n+V5OyD/Ymx5M9NbHZXrpvf0hw3Hvf+zNDTTzapbAmrf844gCtnkP83Rv76m6kMHP7uFkTQ9ba+sD\nmYI97392fGXp+mie2m13vzB7bO2xu7+feuMAAKCzi+4Guk7qlufei3UXOoQGQ/rzxlI9/fbnqg+R\nerskuHSsuk4vF4U+YK5nWrJ+d9PgoEubpcaQfKS6LtIu+5j7f5svBTeD3+pdZbbCS9PwbjLD4nVD\nzlF+/55RDzWBnheL0kpNhasbLjWGvlDjB6GZJ3tbGV2BxikAAEBnQ8iOgs8rqmPdhQ7lybd3a8wT\n67R6V1nAn6/eVaafvbIt7Ozzkeo6vV96JAo9bOmN4q/CBr/h5/ewHF5M8VbHOVwAc8m/9JrT7NQN\nR2TMk73tiLdxCgAA0JYI2Q7LeWhlrLvQIZVXfjsDbKpvMPTuF4f10LKdNu5kLdJmpiXZCr9N756Z\nlqSjIWbDzeC3df8xzZ2aa+vQtnir49w0gDX/fUW7tJLU9nXDOyuzNFpmWpKl9vE2TgEAANoSIdtB\nX5SfiLicFKwxl/6u3lWmsQvW6ba/vO9XRiuc/P49w868ejJSdOeo823/W5r3vGHIOZbaV1TVaEKu\nR927WQsu0ZwRbg0zgHnc/sHK4+4a9UOwYr1cvTOZlJetzXOuUmZactA20V65AAAA0B5w8JmDrnmm\nMNZd6NDMGeCF677QU29/bjsEZ7u7atR3emru1Fzdu3hbi5PGze9rzjToqf/3he3+eZqUAHvh3X1h\n22eld9WW0qMh94g3Fc0Z4daK5CA2J075Nperh6sbboY+ThZvneTEBD1+Q17IEnLxPE4BAADaAiHb\nQacbYt2DzuHFd0sjWjFg/vFvzrw2P/nb/Y96z1ZDb1OPTrlYPx6T4yvbZTX4WT2d+6dj+tmaEY5F\nmLRzardTJcjM5erBPjSRvv13p0a2M4L998fD7xIAAEASIdtRSQkE7bZgZ3m41Bi2/njrUL8//pvP\nvPZKS9ED//cjSfbv7XF39QVsU7D60c2DX6+0FEvPGX9Rb8t9ivcwabfkVjhWQp/Tz+zs2rqEHAAA\nQHtCyHZQPRuyo8olyZ2aZDtkz7pygCYP6tPi9aYzr0V7jqi80t7hWIGWxwYKuE21mO2zmkkstov3\nMBmu5JZLkdVZvkIJ7QAAIABJREFUDhX6ovXMzo564wAAAIFx8JlDDhw+GbaEVDxK6tI+QoXZy7vH\n9LN9bc7ZaWHbRHL6dPODvcyAGyxg/+Kq72rTg+P9Qu7hE7WWnmWlXXuoGR3NklvB6oZT5gsAAABt\niZlsh0x6un0cejb8vO7qlpIol6SdX3p1zOascFtwSUpN7qKTdfW+19ypSbp7TD/de8UFWvrBwZCh\nqTkrJ0tbPX360SkXq1d6SovlsaECrtT4npZ+cEAzx18Q0XOttLMTJmM1AxmLkluU+QIAAEBbImQ7\n5FQ72Yy99cDxWHchLEPSybp6DT+/u/ZUVOv4qdM6fuq0nnx7t5Z+cFA/GJytP28stXSv7qlJlsoJ\nWT2luvnea1OkAdfu6dihtIcwGYuSW5T5AgAAQFtiubhDUpP4VTpt6/7jLfZfl3tr9NzGUl07yNq+\n4rvH9LO0z9Y8pVpquf3ZSmmiSANua5/bVHsIk+aHCuEcq65z/JmhaqNT2xkAAABOIRk6ZPWsy2Pd\nhU7BnO3duv+YeqeHPpm7R7ckzRw/wO+1+gZDRXuO6O/Fh1S054jf/mTzlOreGf737Z2REvbAsNYE\nXPO5nmbhs/me73CiFSZD/c7s6pLg0qNTLg7b7rGVzu0dd/KDDAAAACAclos75Lxe3ZSYIJ1pH6vG\nYybBpVYfEGcuvf7FVQP01D/KZDW/pUtSwQ8H+gUn66WtgkWx4Fq77NuJkkh2akZbFY1yYD0slC1z\neu84tZ0BAADQVlyGYcT9mdiVlZVyu93yer3KyMiIdXdCuuDhlQTtJlySMtOS9espF8vjTtWRqlrN\nXLrdkXs/fcsQpSQmWAqBwUpbmXFz0e3DJClsm1BhzHyGFDjgtlX5LKeCcbDfmenZW4cGLI0Wzt+L\nD2nW0uKw7Z6+ZYiuG3KO7fuHUt9gUNsZAAAAlkSaQwnZUTD+9xu093B1rLvhiNzsdD0yOVcP/N+P\n9HVl4FnaYJqHy1U7vtKvlu1QdW19yOusWnLPKOX37xk2ONU3GBq7YF3Qg8nMWWbDMFReGbhUltlm\n04PjQ4ayaMz8RqK1YTLc70xqXJWwcNowTba4P95UtOeIpj2/OWw7898XAAAAiIVIcyjLxaOg/9lp\nHSZkf11Zq1H9e2reD3J9s7RWubsl6YkfDtSkvGwVrCqxfCJ4OM2XXpv1kYOxevJ3KFbLXzmx7NsJ\n4X4n4YT7nUmNy/5/9so2/SnB3gy9kyeqAwAAAPGGg88cVlpRrY2ffxPrbjjmSHWdtpQe9e1pzUxL\nsnxtalIXTcj1aNWOMkcDtmRvb3Fb11w2A+51Q85Rfv+e7XI5sp3f2fwV9g4p4yAyAAAAdGS2QnZB\nQYFGjBih9PR0ZWVl6frrr9dnn30W8pqXXnpJLperxVdNTexq9UbLd+as1Pf/sEG19XG/At+Wcu8p\nFe05otozDZo28jzL15V5a7R5zxH9+u+7In5285xl98RtKTY1l9s7O+/TnOG3w6kT1QEAAIB4Y2u5\neGFhoWbMmKERI0bozJkzeuSRRzRx4kSVlJQoLS0t6HUZGRktwnjXrh0rrHxnzspWn5odrx5b+YmO\nRli3uGjv4YiuNbP1wmnD1CMtuVVLr60uTzYMQ19X1rKEWd/+zsItGTdFslogXpbWAwAAAE6yFbJX\nr17t9/2LL76orKwsbd26VePGjQt6ncvlksfjiayH7UBpRXWHDdiSIg7YkvT51yciui5QaaVID/Oy\nWtpKkiPlrzrCCdbm72y6xX34kc7wt3bvOAAAABBvWnXwmdfrlSRlZoae3Ttx4oTOP/981dfXa8iQ\nIXrsscc0dOjQoO1ra2tVW/vtKc+VlZWt6WbUTXq6MNZdiFtrSr621f4nY/ppQq6nRTANdGq3JyNF\n00aep3690sKGWat1kltbSzleThd3wqS8bD1761DNXLI95IdImWlJKq+sUdGeI+3yAwUAAADASRGX\n8DIMQ9ddd52OHTumd955J2i7zZs364svvtDAgQNVWVmpp59+WqtWrdJHH32kAQMGBLxm3rx5mj9/\nfovX47WEV7+HVsa6C+2eOzVRC24cFDCIhqvXbLISZq3MMkc6E22lFnd7C9qStGpHmX72irUZ7fb6\ngQIAAADQXJvXyZ4xY4ZWrlypTZs2qW/fvpava2ho0LBhwzRu3Dg988wzAdsEmsk+99xz4zZkX/jI\nqg532FlbunZQtp6+ZWjAIGulXrMplmHWai3ucHW241WgGfpA2vsHCgAAAIAp0pAdUQmv++67T8uX\nL9f69ettBWxJSkhI0IgRI7R79+6gbVJSUpSRkeH3Fc9Wz7o81l1olzK7JenZW4dp4a3DggZPK/Wa\nTebHHFZKStU3GCrac0R/Lz6koj1HbJWgiqSfZp3tzXuOtOo5sTIpL1ubHhyvJfeM0pM/GqzMtOSA\n7ez8GwAAAAAdka092YZh6L777tPrr7+uDRs2KCcnx/YDDcNQcXGxBg4caPvaeJWTlaYElzr04WfR\n8B+3DtOYC3qFbGP31GozzG4pPRr0QK1o7Ju22s8Zr2zTEzcObJezvOYhZUV7joQ8DM/KvwEAAADQ\nUdmayZ4xY4YWL16sV155Renp6SovL1d5eblOnTrla3PnnXdqzpw5vu/nz5+vt956S3v37lVxcbF+\n+tOfqri4WNOnT3fuXcSBvQVTWtR0RmiHT9SGbRPpqdXBQq+5b7r5rHO5t0b3Lt6m1bvKInqe1X4e\nP3W6Vc+JB1Y/UIikrBcAAADQ3tkK2YsWLZLX69UVV1yh7Oxs39err77qa3PgwAGVlX0bII4fP65/\n/ud/1sUXX6yJEyfq0KFD2rhxo0aOHOncu4gTewumaP3sK2LdjXajV1pK2DYjczLlyQjfrrlAobe+\nwdD8FSUBD1Br7TJns6601c9Z2vNyaqsfKET6AQkAAADQntleLh7Ohg0b/L5/8skn9eSTT9rqVHuW\nk5WmXmlJOlx9OtZdiarmtaQjvkkYXRJcmjbyPD35dvA9/M1v6XE3ngjenNV905Esc25aizucSJ8T\nL/W3zQ8Uyr01AcdAqH8DAAAAoKNrVZ1sBNbRA/ZPx/TTql3lfoG1Z1qyrhvSRxNyPVrzcblefG9f\n2PtYWS4uSf16pdnq39ypuQHDZ7SXOZu1uB9atlPHT4UfA3aeE0/1t5t+oND8wxbztx7s3wAAAADo\n6AjZDvvuI6ti3YWouyrXo4en5IacVbUSsp1edpyZlqTHbwh+qJiTzws2qzwpL1vpXZN021/ed+Q5\nUvD62+Y+8liUyzI/UGge/D3UyQYAAEAnR8h20HcfWaW6Dlwvu+kyYPOk6UCOVdeFPG3d7nLicMuT\npcaZ9KI5Vyo5MfgxA04tcw43qzzqOz0dW04dbh+5S437uyfketp85nhSXrYm5HriYgk7AAAAEC8i\nqpONlg4dPdWhA7bUGOoenXJxyBC1eleZZryyLWw5MzvLic3lyVLLbdyuf3z95oa8kAHbyn2s9MvK\n6eROPMdkZx95LJgftlw35Bzl9+9JwAYAAECnR8h2yDXPFMa6C47qnpoU8PXHVn4StPxUqFlXU4JL\n+uOtQ20vJzaXJ3vc/kusPe6utpZLt+Y+dk4nd6q/lMsCAAAA2heWizukurY+1l1w1I9H99NT/6/l\nid6h9gGHm3WVGpeQ97BQuisQp5YnR3ofu6eTO9FfymUBAAAA7Qsh2yFpKV1UWRPfQbt7tyT9x81D\n9atlO/R1ZfD9wr0zUrT0g4MB7xFsH3B9g6F3v/jGUj9aM+sabC+43fJWofaUBxPJrHIkz2mKclkA\nAABA+8JycYe8+fPLY92FsI6fPK3ExATN+0Ho/cLTRp6n8krr+4BX7yrT2AXrtHD9Hkv9cHrW1Xz+\ntOc3a9bSYk17frPGLlgXdFl7pGIxq+zk/m4AAAAA0UfIdsg5malK7hL/QaeiqibsfmGrdanf/eIb\nrdrxVcCDwAJxqfEUbidnXa0cROYUc1Y52L9yNN6f5Nx+dAAAAADRx3JxB33wyAQN/rc1se5GSL3+\nsR861H7hoj1HLN1r4fo9SnAp5EFnpmjMurZ1eStzVvnexdvkkv/7jvasMuWyAAAAgPaBkO2gn7y0\nJdZdCK9JJgu2X9hKXWpTuFJdJk+TOtJOsXoQ2eY9RzRmQC9HnmnOKjevkx2N99dca/d3AwAAAIg+\nQraDvrKwZDrWDp+oDdsm1IxtJK4f0ke/vWlw2DrWdlk9iGzGK9v0xI0DHQvAzCoDAAAACIY92Q7q\n447/Mkq9LJbPCrYPOBJvFH+ly3+3Puz+6PoGQ0V7jujvxYdUtOeI6sNMk1s9YOz4qdOO7882Z5Wv\nG3KO8vv3JGADAAAAkETIdtRffzwy1l0Iz0YWnJSXrU0PjtfM71/Q6seGO4gskhPCwx1E1tz8FSVh\ngzsAAAAAtAYh20Hubkk6v2dqrLsRkpXl4s316JbU6uea0TZQ0I30hPCm5a2sPL9p2TEAAAAAiAZC\ntsMKfzVeZ6XE76/VTg1nc3b5sZWfhG1rZbV0oKAb7oRwKfQMtLmsvXuqtQ8CrO7jBgAAAIBIxG8a\nbMc+eGRiTJ6bmZYUcul0925Jlms4B5tdbs71j6+F04ZZXlbeNOhaPSE81Az0pLxs/fG2YZaebedD\nBgAAAACwi5AdBanJXdTrrNYvsbbrhiHnhDwJ/PjJ01pbUh72PqFml5vzuLtq0e3DNHlQtsZcYK1M\nVtOga3VmOVy7Ud/pGXJ/tktStrur5Q8ZAAAAACAShOwo2fDL8W3+zPEX9Vb3EPunXfp26XWok7zD\nzS6bHp1ysTY9ON5XGivcQWSBgq7VmeVw7Zruz27+fPP7uVNzOQUcAAAAQFRRJztKzuqaqEF9M7Tj\ny8o2eV5mWpLkapytDsZcer1w3Rda+sEBvyCd7e6quVNzNSkv2/Lscq/0FL/QGqq+drCgawbzcm9N\nwJlzlxpny63MQJv7s+evKPF7b54m7w0AAAAAosllGEbc1zSqrKyU2+2W1+tVRkZGrLtjy5SnN+jj\nsuqoP+enY/pp0LndNWtpcUTXm7F30e3D5E5N1rTnN4e9Zsk9o5Tfv2eL11fvKmsRdLNDBF1z/7cU\nOJgvun2YrYBc32BoS+lRVVTVKCu9MaAzgw0AAADAjkhzKCG7Ddz94hat/+ybqD5jyT2j1NBg6LYX\n3o/4HuasceGvvq/Lf7c+7OzypgfHBw2vdoOu3WAOAAAAANEUaQ5luXgbePHukbrn5Q+0tqQibNsE\nl3TziL7a+PlhHToeftl20+XUm/ceaVU/zeXkW/cfs73su7kuCa6As9zBTMrL1oRcDzPQAAAAANo1\nQrZDtnxxVD/6S1HAn2WldVGvjG4a/Z1MHTharS+P1wa9zz3fy9G/TLpYW0qP6i/v7NG6T78Je8q3\nGXgPnwh+Xzsqqmp03ZBz2nx/s91gDgAAAADxxlbILigo0GuvvaZPP/1UqampGj16tBYsWKALL7ww\n5HXLli3To48+qj179qh///76zW9+oxtuuKFVHY8n/R5aGfLnFdX1qqiu8n3ffHbYlNSlcdZ27IJ1\nfsE2WPsEV2MoNwPvvsMnbfY8MPMkb2aXAQAAAMAeWyW8CgsLNWPGDG3evFlr167VmTNnNHHiRFVX\nBz/Yq6ioSDfffLPuuOMOffTRR7rjjjv0ox/9SO+/H/ne4XgSLmAHEmxm+nS9oT9vLG1RPitY+wZD\nem5jqVbvKtPqXWV66u3PbfelqUAltszZ5euGnKP8/j0J2AAAAAAQQqsOPvvmm2+UlZWlwsJCjRs3\nLmCbm2++WZWVlXrzzTd9r02aNEk9evTQkiVLLD0nXg8+C7VEvK24JPXOSJFhSF9XRb5cPJKTvDnF\nGwAAAEBHFZODz7xeryQpMzN4DeOioiL94he/8Hvt6quv1lNPPRX0mtraWtXWfhsYKyvbpta0XbEO\n2FLjLHd5pf1wneBqnAk3hdprHShMry0p5zRwAAAAAGgm4pBtGIZmz56tsWPHKi8vL2i78vJy9e7d\n2++13r17q7y8POg1BQUFmj9/fqRdgwV35fdT3x6pykxLlsedGnQWOlBpre7dknT85OkWbcu9Nbp3\n8Tbbda0BAAAAoKOwtSe7qZkzZ2rHjh2Wlny7XP7hzTCMFq81NWfOHHm9Xt/XwYMHI+0mmjFz9Ivv\n7dNjKz/Rb9/6TN5TdUED9r2Lt7XYIx4oYEvf7h2fv6JE9Q1xX34dAAAAABwXUci+7777tHz5cq1f\nv159+/YN2dbj8bSYta6oqGgxu91USkqKMjIy/L7i0f/5X/mx7oJl3ZK7SPJfIi411sWevnibVu34\nyu/1+gZD81eUhC0f1pxZa3tL6dHIOwsAAAAA7ZStkG0YhmbOnKnXXntN69atU05OTthr8vPztXbt\nWr/X1qxZo9GjR9vraRwaeUHwvejxJjkx9D/1zCXbtWpHme/7LaVHW8xg21FRFfm1AAAAANBe2QrZ\nM2bM0OLFi/XKK68oPT1d5eXlKi8v16lTp3xt7rzzTs2ZM8f3/axZs7RmzRotWLBAn376qRYsWKC3\n335b999/v3PvIob2PTHF9jVtfQD3TcPOCbrE29RgSD97ZZtW72oM2q0NyWatbQAAAADoTGyF7EWL\nFsnr9eqKK65Qdna27+vVV1/1tTlw4IDKyr6dER09erSWLl2qF198UYMGDdJLL72kV199VZdddplz\n7yLG9j0xJeTS8ay0LsrNTteFWWk6K6VLiyXb0ZTt7qoxA8623N7cTx1pSA5UaxsAAAAAOotW1clu\nK/FaJ9uOglUl+vPG0jZ7XtO61+7UZE17frPla5fcM0ojczI1dsE6lXtrbO/LfvbWoZo8qI/NqwAA\nAAAgfkSaQyM+XRzW/U/xV20asKXGutdmKa2ROZnKdlufma6oqlGXBJfmTs2V9G1gN5nfd++WFPD6\nx1Z+4lt2DgAAAACdCSE7ylbtKNN9r25vk2c9OuViPX3LEC25Z5Q2PTjeV6u6aWC2wlwqPikvW4tu\nHyZPs4DucXfVn24fpsevHxjwerNeNkEbAAAAQGeTGOsOdGSrd5XpZ69sa5NnZbu76sdjcgLWu5Ya\nA/Oztw7VzCXbg+4Jd6kxQDfdTz0pL1sTcj3aUnpUFVU1ykr/9udjF6wLeB/jH/eav6JEE3I9QfsE\nAAAAAB0NITtK6hsMzf4/H7XZ8x6dcnHYMDt5UB8tlCtg8DevnDs1t8V9uiS4lN+/p99rRXuOhCzx\n1bRedvNrAQAAAKCjYrl4lMxaul0n6+rb7Hk90lIstZs8KFt/un1Yiz3aTfdwW2G1xBf1sgEAAAB0\nJsxkR0HdmQb9z4623Y9sJ8wGWwJuZ1m31RJf1MsGAAAA0JkQsqPg2mfeafNnBguz9Q1GwDAdaAm4\nHeaJ5cFKfAXa3w0AAAAAHR0h22H3vPyBPq840WbPCxVmV+8q0/wVJX57p7PdXTV3aq7lZeHBmCeW\n37t4m1ySX9AOtb8bAAAAADoy9mQ76FRdvdaWVDh6zykDPXr21mFyqWW9aqkx3E7Oa1z6Xd/k2PDV\nu8p07+JtLQ4nc7K8VqgSX3b2dwMAAABAR+EyDCNIQaf4UVlZKbfbLa/Xq4yMjFh3J6hH39ipv20+\n4Nj9BvXN0PKZ35MUeFY6wSW/clzmLPWEXI/GLlgX9PRvc/Z704PjHZlpDrYkHQAAAADaq0hzKMvF\nHbTvyElH7/dNVZ3qGwx1SXD5HVa2tqRcf313X4t61+Ys9f1XfbdNy2u1dn83AAAAAHQULBd3UL+e\n3Ry9nxmETV0SXBqZk6k3d5UHbG9m7hffK7V0f8prAQAAAICzCNkOenhyruP3bB6Et5QeDTtLffzk\naUv3prwWAAAAADiLkO2gSU8XOn7Pw1W1fgeaWZ197p6aFPCgNKlxT3Y25bUAAAAAwHGEbId4T57W\n/iOnHL/vYys/0dgF63yngVudfb57TD9JLU8kp7wWAAAAAEQPIdshP3lpS9Tu3bTs1sicTGW7u4ad\npZ45fgDltQAAAACgjXG6uEO+CrFPurUMNYbn+StKNCHXo7lTc3Xv4m1y6dvDzqSWs9RNTySnvBYA\nAAAARB8z2Q7p447uIWJNy25Nysu2PEttlte6bsg5yu/fk4ANAAAAAFHETLZD/vrjkRr8b2tsXdN8\nJtoK8+AzZqkBAAAAIP4Qsh3i7pak83um2jr8zJ2apLvH5Oh0fb0Wrt9j6ZqmB5+Zs9QAAAAAgPjA\ncnEHFf5qvM7vmWq5/fFTp/XU25/rZF29pfbdU5MouwUAAAAAcYyQ7bDCX43XLSPOtXXN34u/stTu\n7jH9WA4OAAAAAHGMkB0FA7LOstzWkHSkuk6ZaUlBy3JJUo9uSZo5fkCr+wYAAAAAiB7bIXvjxo2a\nOnWq+vTpI5fLpTfeeCNk+w0bNsjlcrX4+vTTTyPudDw7cPik/n3NZ7avu2HIOZIUMGi7JBX8cCCz\n2AAAAAAQ52wffFZdXa3Bgwfr7rvv1o033mj5us8++0wZGRm+788++2y7j457Fzy8UmcaIrv2qlyP\nRuRkav6KEpU1qbmd7e6quVNz/cpyAQAAAADik+2Qfc011+iaa66x/aCsrCx1797d9nXtRaQB26XG\n+tZm+S3KcgEAAABA+9VmJbyGDh2qmpoa5ebm6te//rW+//3vt9Wjo+7A4ZMRz2AbkuZOzfUFacpy\nAQAAAED7FfWQnZ2dreeee07Dhw9XbW2t/va3v+nKK6/Uhg0bNG7cuIDX1NbWqra21vd9ZWVltLvZ\nKpOeLoz42l9cNYCl4AAAAADQQUQ9ZF944YW68MILfd/n5+fr4MGD+v3vfx80ZBcUFGj+/PnR7ppj\nTp2OcBpbUr9eaQ72BAAAAAAQSzEp4TVq1Cjt3r076M/nzJkjr9fr+zp48GAb9s6+1KTIf41Z6V0d\n7AkAAAAAIJZiErK3b9+u7OzgS6RTUlKUkZHh9xXPVs+63PY1LjWeHD4yJ9P5DgEAAAAAYsL2cvET\nJ07oiy++8H1fWlqq4uJiZWZm6rzzztOcOXN06NAhvfzyy5Kkp556Sv369dMll1yiuro6LV68WMuW\nLdOyZcucexcxdl6vbkpMkO3Dz5oeeAYAAAAAaP9sh+wPP/zQ72Tw2bNnS5LuuusuvfTSSyorK9OB\nAwd8P6+rq9Mvf/lLHTp0SKmpqbrkkku0cuVKTZ482YHux48vHp9iq4zXP4/L4cAzAAAAAOhgXIZh\nGLHuRDiVlZVyu93yer1xv3T8wOGTuvqpDTp1Jviv1ayNvenB8cxkAwAAAEAcijSHxmRPdkd2Xq9u\neu6OESHbGJLKvDXaUnq0bToFAAAAAGgTUS/h1dkUrCrRcxtLLbWtqKqJcm8AAAAAAG2JkO2gglUl\n+rPFgC1J+w6ftP2M+gZDW0qPqqKqRlnpjaeTs+QcAAAAAOIDIdshdWca9Pw71gO2JC394IBmjr/A\nckhevatM81eUqMz77Qx4trur5k7N5RA1AAAAAIgD7Ml2yN+K9qnB5hFydvZlr95VpnsXb/ML2JJU\n7q3RvYu3afWuMnsPBwAAAAA4jpDtkP1H7S/9lqzty65vMDR/RYkCZXjztfkrSlRvN+UDAAAAABxF\nyHbI+ZndIrouK71r2DZbSo+2mMFuitPKAQAAACA+ELIdckd+P9k5f8ylxv3UI3Myw7a1ego5p5UD\nAAAAQGwRsh2SnJige76XY6mtmcXnTs21dOiZldluO+0AAAAAANFByHbQAxMvkpXJ7Kz0ZC26fZjl\nE8FH5mQq29016L3tzIoDAAAAAKKHkO2gvxXtC3g4WXP/63v9bZXc6pLg0typuZLUImjbnRUHAAAA\nAEQPIdtBVk8YP3jM/knkk/Kytej2YfK4/ZeEe9xdbc2KAwAAAACiJzHWHehIrJ4wfm6P1IjuPykv\nWxNyPdpSelQVVTXKSm9cIs4MNgAAAADEB2ayHWT1hPEXNu3T6l1lET2jS4JL+f176roh5yi/f08C\nNgAAAADEEUK2g6yeMP51ZY3uXbwt4qANAAAAAIhPhGyHzZmcq/89LifkKePm4WjzV5SovsHKUWkA\nAAAAgPaAkB0Fcybn6uWfjAzZxpBU5q3RltKjbdMpAAAAAEDUEbKj5OjJOkvtKqpqotwTAAAAAEBb\nIWRHSVZ61/CNbLQDAAAAAMQ/QnaUjMzJVLa7a9C92S5J2e7GElwAAAAAgI6BkB0lXRJcmjs1V5Ja\nBG3z+7lTcynBBQAAAAAdCCE7iiblZWvR7cPkcfsvCfe4u2rR7cM0KS87Rj0DAAAAAERDYqw70NFN\nysvWhFyPtpQeVUVVjbLSG5eIM4MNAAAAAB0PIbsNdElwKb9/z1h3AwAAAAAQZbZD9saNG/W73/1O\nW7duVVlZmV5//XVdf/31Ia8pLCzU7Nmz9fHHH6tPnz76l3/5F02fPj3iTsejh//7Pb3y4TG/11KT\nEnTNJVlKSUrSl8dPqV/Pbnp4cq5Sk7vEqJcAAAAAgGiyHbKrq6s1ePBg3X333brxxhvDti8tLdXk\nyZN1zz33aPHixXr33Xf1s5/9TGeffbal69uDfg+tDPj6qdMNeq243Pf9O7ulv20+oAm5WXr+zhFt\n1T0AAAAAQBtxGYZhRHyxyxV2JvvBBx/U8uXL9cknn/hemz59uj766CMVFRVZek5lZaXcbre8Xq8y\nMjIi7W5UBAvY4RC0AQAAACB+RZpDo366eFFRkSZOnOj32tVXX60PP/xQp0+fjvbjo+rh/34v4mvX\nllToVF29g70BAAAAAMRa1EN2eXm5evfu7fda7969debMGR0+fDjgNbW1taqsrPT7ikfN92Db9fiq\nEod6AgAAAACIB21SJ9vl8i9XZa5Qb/66qaCgQG632/d17rnnRr2PsbDvyMlYdwEAAAAA4KCoh2yP\nx6Py8nK/1yoqKpSYmKiePQOXtZozZ468Xq/v6+DBg9HuZkz069kt1l0AAAAAADgo6iE7Pz9fa9eu\n9XttzZrOxJsCAAALu0lEQVQ1uvTSS5WUlBTwmpSUFGVkZPh9xaNbL+3RqusfnpzrUE8AAAAAAPHA\ndsg+ceKEiouLVVxcLKmxRFdxcbEOHDggqXEW+s477/S1nz59uvbv36/Zs2frk08+0V//+le98MIL\n+uUvf+nQW4idx28aHfG1E3KzqJcNAAAAAB2M7ZD94YcfaujQoRo6dKgkafbs2Ro6dKj+9V//VZJU\nVlbmC9ySlJOTo1WrVmnDhg0aMmSIHnvsMT3zzDMdpkb2viem2L6G8l0AAAAA0DG1qk52W4nnOtmm\nh//7vRanjacmJeiaS7KUkpSkL4+fUr+e3fTw5FxmsAEAAAAgzkWaQwnZAAAAAAA0E2kObZMSXgAA\nAAAAdAaEbAAAAAAAHELIBgAAAADAIYRsAAAAAAAcQsgGAAAAAMAhhGwAAAAAABySGOsOWGFWGaus\nrIxxTwAAAAAAnYGZP+1WvW4XIbuqqkqSdO6558a4JwAAAACAzqSqqkput9tye5dhN5bHQENDg776\n6iulp6fL5XLFujsBVVZW6txzz9XBgwdtFSoHTIwhtBZjCK3FGIITGEdoLcYQWsupMWQYhqqqqtSn\nTx8lJFjfad0uZrITEhLUt2/fWHfDkoyMDP7HAK3CGEJrMYbQWowhOIFxhNZiDKG1nBhDdmawTRx8\nBgAAAACAQwjZAAAAAAA4pMu8efPmxboTHUWXLl10xRVXKDGxXazCRxxiDKG1GENoLcYQnMA4Qmsx\nhtBasRxD7eLgMwAAAAAA2gOWiwMAAAAA4BBCNgAAAAAADiFkAwAAAADgEEI2AAAAAAAOIWQ74Nln\nn1VOTo66du2q4cOH65133ol1lxAnNm7cqKlTp6pPnz5yuVx64403/H5uGIbmzZunPn36KDU1VVdc\ncYU+/vhjvzbHjh3THXfcIbfbLbfbrTvuuEPHjx9vy7eBGCooKNCIESOUnp6urKwsXX/99frss8/8\n2tTW1uq+++5Tr169lJaWph/84Af68ssv/docOHBAU6dOVVpamnr16qWf//znqqura8u3ghhZtGiR\nBg0apIyMDGVkZCg/P19vvvmm7+eMH9hVUFAgl8ul+++/3/ca4wjhzJs3Ty6Xy+/L4/H4fs7fRLDi\n0KFDuv3229WzZ09169ZNQ4YM0datW30/j5dxRMhupVdffVX333+/HnnkEW3fvl3f+973dM011+jA\ngQOx7hriQHV1tQYPHqyFCxcG/Plvf/tb/eEPf9DChQv1wQcfyOPxaMKECaqqqvK1ufXWW1VcXKzV\nq1dr9erVKi4u1h133NFWbwExVlhYqBkzZmjz5s1au3atzpw5o4kTJ6q6utrX5v7779frr7+upUuX\natOmTTpx4oSuvfZa1dfXS5Lq6+s1ZcoUVVdXa9OmTVq6dKmWLVumBx54IFZvC22ob9++euKJJ/Th\nhx/qww8/1Pjx43Xdddf5/uhg/MCODz74QM8995wGDRrk9zrjCFZccsklKisr833t3LnT9zP+JkI4\nx44d05gxY5SUlKQ333xTJSUl+vd//3d1797d1yZuxpGBVhk5cqQxffp0v9cuuugi46GHHopRjxCv\nJBmvv/667/uGhgbD4/EYTzzxhO+1mpoaw+12G3/6058MwzCMkpISQ5KxefNmX5uioiJDkvHpp5+2\nXecRNyoqKgxJRmFhoWEYhnH8+HEjKSnJWLp0qa/NoUOHjISEBGP16tWGYRjGqlWrjISEBOPQoUO+\nNkuWLDFSUlIMr9fbtm8AcaFHjx7GX/7yF8YPbKmqqjIGDBhgrF271rj88suNWbNmGYbB/w7Bmrlz\n5xqDBw8O+DP+JoIVDz74oDF27NigP4+nccRMdivU1dVp69atmjhxot/rEydO1HvvvRejXqG9KC0t\nVXl5ud/4SUlJ0eWXX+4bP0VFRXK73brssst8bUaNGiW3280Y66S8Xq8kKTMzU5K0detWnT592m8c\n9enTR3l5eX7jKC8vT3369PG1ufrqq1VbW+u3xAodX319vZYuXarq6mrl5+czfmDLjBkzNGXKFF11\n1VV+rzOOYNXu3bvVp08f5eTk6JZbbtHevXsl8TcRrFm+fLkuvfRS/dM//ZOysrI0dOhQPf/8876f\nx9M4ImS3wuHDh1VfX6/evXv7vd67d2+Vl5fHqFdoL8wxEmr8lJeXKysrq8W1WVlZjLFOyDAMzZ49\nW2PHjlVeXp6kxjGSnJysHj16+LVtPo6aj7MePXooOTmZcdRJ7Ny5U2eddZZSUlI0ffp0vf7668rN\nzWX8wLKlS5dq27ZtKigoaPEzxhGsuOyyy/Tyyy/rrbfe0vPPP6/y8nKNHj1aR44c4W8iWLJ3714t\nWrRIAwYM0FtvvaXp06fr5z//uV5++WVJ8fW3daJjd+rEXC6X3/eGYbR4DQgm3PgJNJYYY53TzJkz\ntWPHDm3atClsW8YRmrrwwgtVXFys48ePa9myZbrrrrtUWFgYtD3jB00dPHhQs2bN0po1a9S1a1fL\n1zGO0NQ111zj+88DBw5Ufn6++vfvr//8z//UqFGjJPE3EUJraGjQpZdeqscff1ySNHToUH388cda\ntGiR7rzzTl+7eBhHzGS3Qq9evdSlS5cWn3pUVFS0+AQFaM48UTPU+PF4PPr6669bXPvNN98wxjqZ\n++67T8uXL9f69evVt29f3+sej0d1dXU6duyYX/vm46j5ODt27JhOnz7NOOokkpOTdcEFF+jSSy9V\nQUGBBg8erKeffprxA0u2bt2qiooKDR8+XImJiUpMTFRhYaGeeeYZJSYmqnfv3owj2JaWlqaBAwdq\n9+7d/E0ES7Kzs5Wbm+v32sUXX+w7cDqexhEhuxWSk5M1fPhwrV271u/1tWvXavTo0THqFdqLnJwc\neTwev/FTV1enwsJC3/jJz8+X1+vVli1bfG3ef/99eb1exlgnYRiGZs6cqddee03r1q1TTk6O38+H\nDx+upKQkv3FUVlamXbt2+Y2jXbt2qayszNdmzZo1SklJ0fDhw9vmjSCuGIah2tpaxg8sufLKK7Vz\n504VFxf7vi699FLddtttvv/MOIJdtbW1+uSTT5Sdnc3fRLBkzJgxLcqYfv755zr//PMlxdnf1o4d\nodZJLV261EhKSjJeeOEFo6SkxLj//vuNtLQ0Y9++fbHuGuJAVVWVsX37dmP79u2GJOMPf/iDsX37\ndmP//v2GYRjGE088YbjdbuO1114zdu7caUybNs3Izs42KisrffeYNGmSMWjQIKOoqMgoKioyBg4c\naFx77bWxektoY/fee6/hdruNDRs2GGVlZb6vkydP+tpMnz7d6Nu3r/H2228b27ZtM8aPH28MHjzY\nOHPmjGEYhnHmzBkjLy/PuPLKK41t27YZb7/9ttG3b19j5syZsXpbaENz5swxNm7caJSWlho7duww\nHn74YSMhIcFYs2aNYRiMH0Sm6enihsE4QngPPPCAsWHDBmPv3r3G5s2bjWuvvdZIT0/3/c3M30QI\nZ8uWLUZiYqLxm9/8xti9e7fxX//1X0a3bt2MxYsX+9rEyzgiZDvgj3/8o3H++ecbycnJxrBhw3yl\ndYD169cbklp83XXXXYZhNJYamDt3ruHxeIyUlBRj3Lhxxs6dO/3uceTIEeO2224z0tPTjfT0dOO2\n224zjh07FoN3g1gINH4kGS+++KKvzalTp4yZM2camZmZRmpqqnHttdcaBw4c8LvP/v37jSlTphip\nqalGZmamMXPmTKOmpqaN3w1i4Sc/+Ynv/6POPvts48orr/QFbMNg/CAyzUM24wjh3HzzzUZ2draR\nlJRk9OnTx/jhD39ofPzxx76f8zcRrFixYoWRl5dnpKSkGBdddJHx3HPP+f08XsaRyzAMw7l5cQAA\nAAAAOi/2ZAMAAAAA4BBCNgAAAAAADiFkAwAAAADgEEI2AAAAAAAOIWQDAAAAAOAQQjYAAAAAAA4h\nZAMAAAAA4BBCNgAAAAAADiFkAwAAAADgEEI2AAAAAAAOIWQDAAAAAOAQQjYAAAAAAA75/0qN/H7s\n/W83AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11b055d90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1, 1, figsize=(12, 4))\n",
    "ax.scatter(df_items_sorted_by_mean_rating_merge['rating_times'],df_items_sorted_by_mean_rating_merge['mean_rating']);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "由上图可见，评分少的不见得就平均分就低，从整体趋势来看，评分次数多的，平均分也高。可见，流行电影确实受人欢迎。从另一个角度看，存在不少广受大众欢迎的电影，但也存在不少看的人不多，但评分很高质量很好的电影，太流行的电影肯定大家都看过了，关键是如何找到那些还比较小众的电影，这些电影可能具备大众欢迎的元素，但因宣传做得不好没被大众发现，也可能是这些电影就是小众，在小圈子里非常受欢迎，但到更大的人群中就不行。如何把这些电影推荐给何时的人，是个性化推荐要考虑的问题。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 计算电影的年份（从title中来）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>item_id</th>\n",
       "      <th>mean_rating</th>\n",
       "      <th>rating_times</th>\n",
       "      <th>title</th>\n",
       "      <th>release_date</th>\n",
       "      <th>video_release_date</th>\n",
       "      <th>imdb_url</th>\n",
       "      <th>unknown</th>\n",
       "      <th>Action</th>\n",
       "      <th>Adventure</th>\n",
       "      <th>...</th>\n",
       "      <th>Musical</th>\n",
       "      <th>Mystery</th>\n",
       "      <th>Romance</th>\n",
       "      <th>Sci-Fi</th>\n",
       "      <th>Thriller</th>\n",
       "      <th>War</th>\n",
       "      <th>Western</th>\n",
       "      <th>ranking_rating_times</th>\n",
       "      <th>ranking_mean_rate</th>\n",
       "      <th>year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1293</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3</td>\n",
       "      <td>Star Kid (1997)</td>\n",
       "      <td>16-Jan-1998</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/M/title-exact?imdb-title-12...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1450</td>\n",
       "      <td>0</td>\n",
       "      <td>1997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1467</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2</td>\n",
       "      <td>Saint of Fort Washington, The (1993)</td>\n",
       "      <td>01-Jan-1993</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/M/title-exact?Saint%20of%20...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1483</td>\n",
       "      <td>1</td>\n",
       "      <td>1993</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1653</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1</td>\n",
       "      <td>Entertaining Angels: The Dorothy Day Story (1996)</td>\n",
       "      <td>27-Sep-1996</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/M/title-exact?Entertaining%...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1652</td>\n",
       "      <td>2</td>\n",
       "      <td>1996</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>814</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1</td>\n",
       "      <td>Great Day in Harlem, A (1994)</td>\n",
       "      <td>01-Jan-1994</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/M/title-exact?Great%20Day%2...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1661</td>\n",
       "      <td>3</td>\n",
       "      <td>1994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1122</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1</td>\n",
       "      <td>They Made Me a Criminal (1939)</td>\n",
       "      <td>01-Jan-1939</td>\n",
       "      <td>NaN</td>\n",
       "      <td>http://us.imdb.com/M/title-exact?They%20Made%2...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1615</td>\n",
       "      <td>4</td>\n",
       "      <td>1939</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 29 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   item_id  mean_rating  rating_times  \\\n",
       "0     1293          5.0             3   \n",
       "1     1467          5.0             2   \n",
       "2     1653          5.0             1   \n",
       "3      814          5.0             1   \n",
       "4     1122          5.0             1   \n",
       "\n",
       "                                               title release_date  \\\n",
       "0                                    Star Kid (1997)  16-Jan-1998   \n",
       "1               Saint of Fort Washington, The (1993)  01-Jan-1993   \n",
       "2  Entertaining Angels: The Dorothy Day Story (1996)  27-Sep-1996   \n",
       "3                      Great Day in Harlem, A (1994)  01-Jan-1994   \n",
       "4                     They Made Me a Criminal (1939)  01-Jan-1939   \n",
       "\n",
       "   video_release_date                                           imdb_url  \\\n",
       "0                 NaN  http://us.imdb.com/M/title-exact?imdb-title-12...   \n",
       "1                 NaN  http://us.imdb.com/M/title-exact?Saint%20of%20...   \n",
       "2                 NaN  http://us.imdb.com/M/title-exact?Entertaining%...   \n",
       "3                 NaN  http://us.imdb.com/M/title-exact?Great%20Day%2...   \n",
       "4                 NaN  http://us.imdb.com/M/title-exact?They%20Made%2...   \n",
       "\n",
       "   unknown  Action  Adventure  ...   Musical  Mystery  Romance  Sci-Fi  \\\n",
       "0        0       0          1  ...         0        0        0       1   \n",
       "1        0       0          0  ...         0        0        0       0   \n",
       "2        0       0          0  ...         0        0        0       0   \n",
       "3        0       0          0  ...         0        0        0       0   \n",
       "4        0       0          0  ...         0        0        0       0   \n",
       "\n",
       "   Thriller  War  Western  ranking_rating_times  ranking_mean_rate  year  \n",
       "0         0    0        0                  1450                  0  1997  \n",
       "1         0    0        0                  1483                  1  1993  \n",
       "2         0    0        0                  1652                  2  1996  \n",
       "3         0    0        0                  1661                  3  1994  \n",
       "4         0    0        0                  1615                  4  1939  \n",
       "\n",
       "[5 rows x 29 columns]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 使用正则表达式取出上映年份\n",
    "df_items_sorted_by_mean_rating_merge['year'] = df_items_sorted_by_mean_rating_merge.title.str.extract('(\\((\\d{4})\\))', expand=True).iloc[:,1] \n",
    "df_items_sorted_by_mean_rating_merge.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#去掉年份后的Title\n",
    "#import re\n",
    "#pattern = re.compile(r'^(.*)\\((\\d+)\\)$')\n",
    "#title_map = {val:pattern.match(val).group(1) for ii,val in enumerate(set(df_items_sorted_by_mean_rating_merge['title']))}\n",
    "#df_items_sorted_by_mean_rating_merge['title'] = df_items_sorted_by_mean_rating_merge['title'].map(title_map)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#统计每年上映的电影数目，默认是降序排列\n",
    "items_sorted_by_year = df_items_sorted_by_mean_rating_merge['year'].value_counts() "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x110745ad0>"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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mzYtHH300Zs+e3aG4iIj58+fHT37yk/jKV74SV199dfzz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\nt4/VEdn2j9XeN0ZUbv+4vuuxVo/VEc4d12c9tlc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shRqqHS8HNayp2vvnPLwOjnO1U4P1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\nAABQSBpjAAAAABSSxhgAAAAAhfT/AH2HSDxvLUbBAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x110a59510>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1, 1, figsize=(15, 12))\n",
    "items_sorted_by_year.plot(kind='bar', title='freq')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.16"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
